Population-based Health Research Research Articles

Catchment area and cancer population health research through a novel population-based statewide database: ascoping review.

Population-based linked datasets are vital to generate catchment area and population health research. The novel Cancer Information and Population Health Resource (CIPHR) links statewide cancer registry data, public and private insurance claims, and provider- and area-level data, representing more than 80% of North Carolina's large, diverse population of individuals diagnosed with cancer. This scoping review of articles that used CIPHR data characterizes the breadth of research generated and identifies further opportunities for population-based health research. Articles published between January 2012 and August 2023 were categorized by cancer site and outcomes examined across the care continuum. Statistically significant associations between patient-, provider-, system-, and policy-level factors and outcomes were summarized. Among 51 articles, 42 reported results across 23 unique cancer sites and 13 aggregated across multiple sites. The most common outcomes examined were treatment initiation and/or adherence (n = 14), mortality or survival (n = 9), and health-care resource utilization (n = 9). Few articles focused on cancer recurrence (n = 1) or distance to care (n = 1) as outcomes. Many articles discussed racial, ethnic, geographic, and socioeconomic inequities in care. These findings demonstrate the value of robust, longitudinal, linked, population-based databases to facilitate catchment area and population health research aimed at elucidating cancer risk factors, outcomes, care delivery trends, and inequities that warrant intervention and policy attention. Lessons learned from years of analytics using CIPHR highlight opportunities to explore less frequently studied cancers and outcomes, motivate equity-focused interventions, and inform development of similar resources.

Association of Traditional dietary pattern with early and precocious puberty: a population-based cross-sectional study.

Precocious puberty is an endocrine disease that is diagnosed by sex, age, and Tanner stage of puberty. This study aimed to investigate the association between various dietary patterns and early or precocious puberty, especially Traditional dietary patterns, which have been rarely investigated. A total of 4085 primary school students in grades 1-3 (6-9 years) completed individual characteristic surveys, health examinations, and food frequency questionnaires (FFQs). Physical examinations were also conducted to assess obesity and pubertal onset. Traditional, Westernized, and Protein dietary patterns were determined by factor analysis, and their associations with pubertal onset were analyzed by multiple logistic regression analysis. Compared to the other two patterns, children who predominant the Traditional dietary pattern were protectively associated with precocious puberty (OR = 0.72, 95% CI = 0.55, 0.94), even after adjusting the confounders (OR = 0.66, 95% CI = 0.48, 0.89). Neither the Westernized nor Protein dietary pattern demonstrated an association with pubertal onset. The Traditional dietary pattern was negatively associated with children's weight status, classified by body mass index (BMI), and was positively associated with parental education. The maternal education and the Protein dietary pattern were negatively related. Traditional dietary patterns were protective associated with early and precocious puberty among Chinese children. The Traditional dietary pattern was protective associated with early puberty or precocious puberty in children, as found in large-scale population-based public health research. Current research primarily focuses on Westernized dietary patterns, and we studied Traditional dietary patterns to further explore the influence of food on children's puberty development. We discovered that children's preference for Traditional dietary patterns is protective of pubertal development, which implies that society and parents can benefit from diet guidance to protect children's natural development during adolescence.

Our health, our research. Identifying public health research priorities among children and youth in a multiethnic population: protocol for a community-based participatory health research priority survey

IntroductionEmphasis on public involvement (PI) in health research has increased in the last 20 years. However, there is limited literature on PI in planning and conducting population-based health research. This...

Widening the lens of population-based health research to climate change impacts and adaptation: the climate change and health evaluation and response system (CHEERS).

Climate change significantly impacts health in low-and middle-income countries (LMICs), exacerbating vulnerabilities. Comprehensive data for evidence-based research and decision-making is crucial but scarce. Health and Demographic Surveillance Sites (HDSSs) in Africa and Asia provide a robust infrastructure with longitudinal population cohort data, yet they lack climate-health specific data. Acquiring this information is essential for understanding the burden of climate-sensitive diseases on populations and guiding targeted policies and interventions in LMICs to enhance mitigation and adaptation capacities. The objective of this research is to develop and implement the Change and Health Evaluation and Response System (CHEERS) as a methodological framework, designed to facilitate the generation and ongoing monitoring of climate change and health-related data within existing Health and Demographic Surveillance Sites (HDSSs) and comparable research infrastructures. CHEERS uses a multi-tiered approach to assess health and environmental exposures at the individual, household, and community levels, utilizing digital tools such as wearable devices, indoor temperature and humidity measurements, remotely sensed satellite data, and 3D-printed weather stations. The CHEERS framework utilizes a graph database to efficiently manage and analyze diverse data types, leveraging graph algorithms to understand the complex interplay between health and environmental exposures. The Nouna CHEERS site, established in 2022, has yielded significant preliminary findings. By using remotely-sensed data, the site has been able to predict crop yield at a household level in Nouna and explore the relationships between yield, socioeconomic factors, and health outcomes. The feasibility and acceptability of wearable technology have been confirmed in rural Burkina Faso for obtaining individual-level data, despite the presence of technical challenges. The use of wearables to study the impact of extreme weather on health has shown significant effects of heat exposure on sleep and daily activity, highlighting the urgent need for interventions to mitigate adverse health consequences. Implementing the CHEERS in research infrastructures can advance climate change and health research, as large and longitudinal datasets have been scarce for LMICs. This data can inform health priorities, guide resource allocation to address climate change and health exposures, and protect vulnerable communities in LMICs from these exposures.

Challenges and Strategies in Conducting Population Health Research during the COVID-19 Pandemic: Experience from a Nationwide Mixed-Methods Study in Bangladesh.

Introduction: Globally, the coronavirus (COVID-19) pandemic poses fundamental challenges in everyday life. Various controlling measures, including nationwide lockdowns, movement restrictions, travel bans, social distancing, and improved hygiene practices, have been widely introduced to curtail transmission of the disease. Notably, these measures have affected the execution of population health research that typically involves face-to-face data collection. This paper details a subjective reflective account of the challenges and mitigating strategies in conducting a nationwide study during the COVID-19 pandemic in 2021. Challenges and strategies: The research team faced a wide range of challenges in conducting this study. The major categories of challenges were defined as follows: (i) challenges relating to the COVID-19 pandemic, such as insufficient access to field sites; (ii) challenges related to contextual factors, such as cultural and gender sensitivity and extreme weather events; and (iii) challenges related to data quality and validity. The key mitigating strategies to overcoming these challenges included engaging a local-level field supervisor, hiring data collectors from respective study sites, incorporating team members' reviews of literature and experts' views to develop research instruments, modifying original research instruments, organizing regular meetings and debriefing, adjusting field operation plans, building gender-sensitive teams, understanding local norms and adopting culturally appropriate dress codes, and conducting interviews in local languages. Conclusions: This paper concludes that despite several COVID-19-related challenges coupled with contextual factors, data were successfully collected through timely and successful adaptations of several mitigating strategies. The strategies adopted in this study may be useful for overcoming unforeseeable challenges in planning and conducting future population-based health research in similar circumstances elsewhere.

A Review of Major Danish Biobanks: Advantages and Possibilities of Health Research in Denmark.

Biobank research may lead to an improved understanding of disease etiology and advance personalized medicine. Denmark (population ~5.9 million) provides a unique setting for population-based health research. The country is a rich source of biobanks and the universal, tax-funded healthcare system delivers routinely collected data to numerous registries and databases. By virtue of the civil registration number (assigned uniquely to all Danish citizens), biological specimens stored in biobanks can be combined with clinical and demographic data from these population-based health registries and databases. In this review, we aim to provide an understanding of advantages and possibilities of biobank research in Denmark. As knowledge about the Danish setting is needed to grasp the full potential, we first introduce the Danish healthcare system, the Civil Registration System, the population-based registries, and the interface with biobanks. We then describe the biobank infrastructures, comprising the Danish National Biobank Initiative, the Bio- and Genome Bank Denmark, and the Danish National Genome Center. Further, we briefly provide an overview of fourteen selected biobanks, including: The Danish Newborn Screening Biobank; The Danish National Birth Cohort; The Danish Twin Registry Biobank; Diet, Cancer and Health; Diet, Cancer and Health - Next generations; Danish Centre for Strategic Research in Type 2 Diabetes; Vejle Diabetes Biobank; The Copenhagen Hospital Biobank; The Copenhagen City Heart Study; The Copenhagen General Population Study; The Danish Cancer Biobank; The Danish Rheumatological Biobank; The Danish Blood Donor Study; and The Danish Pathology Databank. Last, we inform on practical aspects, such as data access, and discuss future implications.

Engagement With mHealth COVID-19 Digital Biomarker Measurements in a Longitudinal Cohort Study: Mixed Methods Evaluation.

The COVID-19 pandemic accelerated the interest in implementing mobile health (mHealth) in population-based health studies, but evidence is lacking on engagement and adherence in studies. We conducted a fully remote study for ≥6 months tracking COVID-19 digital biomarkers and symptoms using a smartphone app nested within an existing cohort of adults. We aimed to investigate participant characteristics associated with initial and sustained engagement in digital biomarker collection from a bespoke smartphone app and if engagement changed over time or because of COVID-19 factors and explore participants' reasons for consenting to the smartphone substudy and experiences related to initial and continued engagement. Participants in the Fenland COVID-19 study were invited to the app substudy from August 2020 to October 2020 until study closure (April 30, 2021). Participants were asked to complete digital biomarker modules (oxygen saturation, body temperature, and resting heart rate [RHR]) and possible COVID-19 symptoms in the app 3 times per week. Participants manually entered the measurements, except RHR that was measured using the smartphone camera. Engagement was categorized by median weekly frequency of completing the 3 digital biomarker modules (categories: 0, 1-2, and ≥3 times per week). Sociodemographic and health characteristics of those who did or did not consent to the substudy and by engagement category were explored. Semistructured interviews were conducted with 35 participants who were purposively sampled by sex, age, educational attainment, and engagement category, and data were analyzed thematically; 63% (22/35) of the participants consented to the app substudy, and 37% (13/35) of the participants did not consent. A total of 62.61% (2524/4031) of Fenland COVID-19 study participants consented to the app substudy. Of those, 90.21% (2277/2524) completed the app onboarding process. Median time in the app substudy was 34.5 weeks (IQR 34-37) with no change in engagement from 0 to 3 months or 3 to 6 months. Completion rates (≥1 per week) across the study between digital biomarkers were similar (RHR: 56,517/77,664, 72.77%; temperature: 56,742/77,664, 73.06%; oxygen saturation: 57,088/77,664, 73.51%). Older age groups and lower managerial and intermediate occupations were associated with higher engagement, whereas working, being a current smoker, being overweight or obese, and high perceived stress were associated with lower engagement. Continued engagement was facilitated through routine and personal motivation, and poor engagement was caused by user error and app or equipment malfunctions preventing data input. From these results, we developed key recommendations to improve engagement in population-based mHealth studies. This mixed methods study demonstrated both high initial and sustained engagement in a large mHealth COVID-19 study over a ≥6-month period. Being nested in a known cohort study enabled the identification of participant characteristics and factors associated with engagement to inform future applications in population-based health research.

Multigenerational health research using population-based linked databases: an international review.

Family health history is a well-established risk factor for many health conditions but the systematic collection of health histories, particularly for multiple generations and multiple family members, can be challenging. Routinely-collected electronic databases in a select number of sites worldwide offer a powerful tool to conduct multigenerational health research for entire populations. At these sites, administrative and healthcare records are used to construct familial relationships and objectively-measured health histories. We review and synthesize published literature to compare the attributes of routinely-collected, linked databases for three European sites (Denmark, Norway, Sweden) and three non-European sites (Canadian province of Manitoba, Taiwan, Australian state of Western Australia) with the capability to conduct population-based multigenerational health research. Our review found that European sites primarily identified family structures using population registries, whereas non-European sites used health insurance registries (Manitoba and Taiwan) or linked data from multiple sources (Western Australia). Information on familial status was reported to be available as early as 1947 (Sweden); Taiwan had the fewest years of data available (1995 onwards). All centres reported near complete coverage of familial relationships for their population catchment regions. Challenges in working with these data include differentiating biological and legal relationships, establishing accurate familial linkages over time, and accurately identifying health conditions. This review provides important insights about the benefits and challenges of using routinely-collected, population-based linked databases for conducting population-based multigenerational health research, and identifies opportunities for future research within and across the data-intensive environments at these six sites.

Development of a computable phenotype to identify a transgender sample for health research purposes: a feasibility study in a large linked provincial healthcare administrative cohort in British Columbia, Canada

ObjectivesInnovative methods are needed for identification of transgender people in administrative records for health research purposes. This study investigated the feasibility of using transgender-specific healthcare utilisation in a Canadian population-based...

A pilot study for exploring blood spot anti-mullerian hormone for population-based adolescent reproductive health research.

Studies of Anti-Müllerian Hormone (AMH) rely upon serum measures and clinical samples of older reproductive-aged women intended/attempting pregnancy, with known fertility issues or medical morbidities. We explored the utility of minimally invasive AMH as a measure of fecundability in population-based reproductive health research. We analyzed baseline data from 191 participants in a pilot, longitudinal cohort study, the Young Women's Stress Study. Using an integrated biosocial design, we collected interviewer-administered surveys on demographic, psychosocial, health, and method feasibility/acceptability information and finger-stick capillary dried blood spots (DBS). We used descriptive and bivariate statistics (correlation, T-tests, ANOVA) to estimate method feasibility/acceptability and unadjusted AMH mean concentrations overall and across sociodemographic, reproductive, and health covariates. AMH concentrations ranged from 1.02 to 22.23 ng/mL, with a mean of 5.66 ng/mL. AMH concentrations were associated with current hormonal contraceptive use, menstrual cycle frequency, and irregular menstrual patterns, but not with other known correlates. Most participants stated the DBS method was comfortable (81%) and would be likely to provide it again (88%). While these pilot data suggest AMH fell within normal range and our DBS methods were acceptable/feasible, the broader question of its usefulness for population reproductive health research remains unanswered. Larger, longitudinal studies are needed to validate AMH against time-to-pregnancy and gold standard measures in young healthy samples and across different sociodemographic groups. Public health and social scientists should consider the resource costs of AMH, ethical issues, and risks of (over)interpretation, with a reproductive justice and human rights frame in mind.

Estimating Attributable Life Expectancy Under the Proportional Mean Residual Life Model

In population-based health research, the so-called population attributable fraction is an important quantity that calculates the percentage of excess risk of morbidity and mortality associated with modifiable risk factors for a given population. While the concept of “risk” is usually measured by event probabilities, in practice it may be of a more direct interest to know the excess life expectancy associated with the modifiable risk factors instead, particularly when mortality is of the ultimate concern. In this paper, we thus propose to study a novel quantity, termed “attributable life expectancy,” to measure the population attributable fraction of life expectancy. We further develop a model-based approach for the attributable life expectancy under the Oakes–Dasu proportional mean residual life model, and establish its asymptotic properties for inferences. Numerical studies that include Monte-Carlo simulations and an actual analysis of the mortality associated with smoking cessation in an Asia Cohort Consortium are conducted to evaluate the performance of our proposed method.

Developing an Environmental Exposure Data Platform for Urban Health Research

An important part of the Canadian Urban Environmental Health Research Consortium’s (CANUE) mandate is developing an operational urban environmental exposure data platform in support of population-based health research. An effective data platform is viewed as key to breaking down some of the existing research silos in the environment and health field and enabling investigation of multiple and interacting environmental influences on population health.In this presentation, we focus on summarizing the types of exposure data in our platform and those we are currently working on, along with how we manage data access and provide user support with value-added content, and custom data processing and visualization tools. In the early stages of developing content for the data platform our efforts focused on integrating data from different national-scale data sources already in existence, many of which were publicly available with published supporting documentation. Continuing efforts focus on developing new data metrics and integrating the many regional and city-specific or, so-called long-tailed data that make up most urban data sets.Our early experience in developing an environmental exposure data platform has provided valuable lessons learned and guided the operation and user support provided by CANUE. In this context, we discuss the data curation process, including data discovery and content selection when presented with multiple datasets. The lessons learned are aimed at data managers that must decide on the value of the data as well as adding value to the data through the curation process. Finally, we discuss some of the emerging challenges in building, sustaining, and future-proofing an environmental exposure data platform for urban health research.

Wildland fire smoke and human health

The natural cycle of landscape fire maintains the ecological health of the land, yet adverse health effects associated with exposure to emissions from wildfire produce public health and clinical challenges. Systematic reviews conclude that a positive association exists between exposure to wildfire smoke or wildfire particulate matter (PM2.5) and all-cause mortality and respiratory morbidity. Respiratory morbidity includes asthma, chronic obstructive pulmonary disease (COPD), bronchitis and pneumonia. The epidemiological data linking wildfire smoke exposure to cardiovascular mortality and morbidity is mixed, and inconclusive. More studies are needed to define the risk for common and costly clinical cardiovascular outcomes. Susceptible populations include people with respiratory and possibly cardiovascular diseases, middle-aged and older adults, children, pregnant women and the fetus. The increasing frequency of large wildland fires, the expansion of the wildland-urban interface, the area between unoccupied land and human development; and an increasing and aging U.S. population are increasing the number of people at-risk from wildfire smoke, thus highlighting the necessity for broadening stakeholder cooperation to address the health effects of wildfire. While much is known, many questions remain and require further population-based, clinical and occupational health research. Health effects measured over much wider geographical areas and for longer periods time will better define the risk for adverse health outcomes, identify the sensitive populations and assess the influence of social factors on the relationship between exposure and health outcomes. Improving exposure models and access to large clinical databases foreshadow improved risk analysis facilitating more effective risk management. Fuel and smoke management remains an important component for protecting population health. Improved smoke forecasting and translation of environmental health science into communication of actionable information for use by public health officials, healthcare professionals and the public is needed to motivate behaviors that lower exposure and protect public health, particularly among those at high risk.

The 2013 Canadian Forces Mental Health Survey: Background and Methods.

The 2013 Canadian Forces Mental Health Survey (CFMHS) collected detailed information on mental health problems, their impacts, occupational and nonoccupational determinants of mental health, and the use of mental health services from a random sample of 8200 serving personnel. The objective of this article is to provide a firm scientific foundation for understanding and interpreting the CFMHS findings. This narrative review first provides a snapshot of the Canadian Armed Forces (CAF), focusing on 2 key determinants of mental health: the deployment of more than 40,000 personnel in support of the mission in Afghanistan and the extensive renewal of the CAF mental health system. The findings of recent population-based CAF mental health research are reviewed, with a focus on findings from the very similar mental health survey done in 2002. Finally, key aspects of the methods of the 2013 CFMHS are presented. The findings of 20 peer-reviewed publications using the 2002 mental health survey data are reviewed, along with those of 25 publications from other major CAF mental health research projects executed over the past decade. More than a decade of population-based mental health research in the CAF has provided a detailed picture of its mental health and use of mental health services. This knowledge base and the homology of the 2013 survey with the 2002 CAF survey and general population surveys in 2002 and 2012 will provide an unusual opportunity to use the CFMHS to situate mental health in the CAF in a historical and societal perspective.

Quality of administrative health databases in Canada: A scoping review.

Administrative health databases are increasingly used to conduct population-based health research and surveillance; this has resulted in a corresponding growth in studies about their quality. Our objective was to describe the characteristics of published Canadian studies about administrative health database quality. PubMed, Scopus, and Google Advanced were searched, along with websites of relevant organizations. English-language studies that evaluated the quality of one or more Canadian administrative health databases between 2004 and 2014 were selected for inclusion. Extracted information included data quality concepts and measures, year and type of publication, type of database, and geographic origin. More than 3,000 publications were identified fromthe search. Twelve reports and 144 peer-reviewed papers were included. The majority (53.5%) of peer-review publications used databases from Ontario and Alberta, while 67% of the non-peer-review publications used data from multiple provinces/ territories. Almost all peer-reviewed papers (97.2%) were validation studies. Hospital discharge abstracts and physician billing claims were the most frequently validated databases. Approximately half of the publications (53.0%) validated case definitions and 37.7% focused on a chronic physical health condition. Gaps in the Canadian administrative data quality literature include a limited number of studies evaluating data from the Maritimes and across multiple jurisdictions, newer data sources, validating methods for identifying individuals with mental illness, and assessing the completeness and serviceability of the data. Data quality studies can aid researchers to understand the strengths and limitations of the data.

Intercultural Competency in Public Health: A Call for Action to Incorporate Training into Public Health Education.

Due to increasing national diversity, programs addressing cultural competence have multiplied in U.S. medical training institutions. Although these programs share common goals for improving clinical care for patients and reducing health disparities, there is little standardization across programs. Furthermore, little progress has been made to translate cultural competency training from the clinical setting into the public health setting where the focus is on population-based health, preventative programming, and epidemiological and behavioral research. The need for culturally relevant public health programming and culturally sensitive public health research is more critical than ever. Awareness of differing cultures needs to be included in all processes of planning, implementation and evaluation. By focusing on community-based health program planning and research, cultural competence implies that it is possible for public health professionals to completely know another culture, whereas intercultural competence implies it is a dual-sided process. Public health professionals need a commitment toward intercultural competence and skills that demonstrate flexibility, openness, and self-reflection so that cultural learning is possible. In this article, the authors recommend a number of elements to develop, adapt, and strengthen intercultural competence education in public health educational institutions.

A Risk Assessment Approach for Policy Evaluation: New Jersey Case Studies

ABSTRACTMonitoring environmental policy progress often focuses on contaminant concentrations while policy goals address health. To bridge this gap, we developed policy evaluation case studies applying risk assessment methods to explore population health risks of chemical exposures before and after policy implementation. Beginning in the 1970s the New Jersey Department of Environmental Protection provided some of the United States' first data on contaminants including trichloroethylene in drinking water and polychlorinated biphenyls (PCBs) in fish. These data provide a unique opportunity to evaluate environmental policies. The 1979 PCB manufacturing ban succeeded in reducing exposure and risk, but the persistence of these compounds in local fish requires continued state and local consumption advisories. The positive impact of drinking water standards for trichloroethylene was reflected in declining detection in public water supplies from the late 1970s to 2005, although maximum concentrations in a small percentage of supplies remain above standards. Our case studies show success and progress, and the need for multiple policies in combination when conditions warrant. Tracking specific policies and contaminants using risk assessment methods can be a valuable tool for policy evaluation and can foster population-based environmental health research. Pollution prevention policies are warranted for chemicals that persist in the environment.

Health & Demographic Surveillance System Profile: The Rufiji Health and Demographic Surveillance System (Rufiji HDSS).

The Rufiji Health and Demographic Surveillance System (HDSS) was established in October 1998 to evaluate the impact on burden of disease of health system reforms based on locally generated data, prioritization, resource allocation and planning for essential health interventions. The Rufiji HDSS collects detailed information on health and survival and provides a framework for population-based health research of relevance to local and national health priorities.In December 2012 the population under surveillance was about 105,503 people, residing in 19,315 households. Monitoring of households and members within households is undertaken in regular 6-month cycles known as 'rounds'. Self reported information is collected on demographic, household, socioeconomic and geographical characteristics. Verbal autopsy is conducted using standardized questionnaires, to determine probable causes of death. In conjunction with core HDSS activities, the ongoing studies in Rufiji HDSS focus on maternal and new-born health, evaluation of safety of artemether-lumefantrine (AL) exposure in early pregnancy and the clinical safety of a fixed dose of dihydroartemisinin-piperaquine (DHA-PQP) in the community. Findings of studies conducted in Rufiji HDSS can be accessed at www.ihi.or.tz/IHI-Digital-Library.

Validation of Health Event Capture in the Marshfield Epidemiologic Study Area.

In this study, health event capture is broadly defined as the degree to which a group of people use a particular provider network as their primary source of health care services. The Marshfield Epidemiologic Study Area (MESA) is a valuable resource for population-based health research, but the completeness of health event capture has not been validated in recent years. Our objective was to determine the current level of outpatient and inpatient health event capture by Marshfield Clinic (MC) facilities and affiliated hospitals for people living within MESA. A stratified sample survey with strata defined by MESA region (Central or North) and age group (<18 years or ≥18 years). 24 ZIP codes in central and northern Wisconsin, USA. 2,485 individuals participated of the 4,313 sampled cohort members residing in MESA Central (N=61,041) and MESA North (N=25,906) on February 22, 2011. A health care utilization survey was mailed to a random sample stratified by age group and MESA region. Telephone interviews were attempted for nonrespondents. The survey requested information on sources of outpatient care and overnight hospital admissions. Population proportions representing health event capture metrics and corresponding 95% confidence intervals (CI) were estimated with analytic weights applied to account for the survey design. Among those with an outpatient visit during the past 24 months, the most recent visit of an estimated 93% (95% CI, 91% - 94%) was at a MC facility. The most recent admission of an estimated 93% (95% CI, 90% - 96%) of those hospitalized in the past 24 months was at a hospital affiliated with MC. The proportion admitted to MC affiliated hospitals was higher for residents of MESA Central (97%) compared to MESA North (83%). A high proportion of outpatient visits and inpatient admissions in MESA Central and MESA North are accessible in the MC electronic health record. This pattern of high health event capture has been demonstrated since the inception of MESA in 1991. The results from this study validate and support the continued use of MESA for population-based epidemiologic and clinical research.

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument

BackgroundThis study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being.MethodsData were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner.ResultsExploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach’s alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes.ConclusionsThis study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies.