Workplace socioeconomic characteristics and coronary heart disease: a nationwide follow-up study.

OBJECTIVES: Important gaps in previous research include a lack of studies on the association between socioeconomic characteristics of the workplace and coronary heart disease (CHD).We aimed to examine two contextual factors in association with individuals' risk of CHD: the mean educational level of all employees at each individual's workplace (educationwork) and the neighbourhood socioeconomic characteristics of each individual's workplace (neighbourhood SESwork). DESIGN: Nationwide follow-up/cohort study. SETTING: Nationwide data from Sweden. PARTICIPANTS: All individuals born in Sweden from 1943 to 1957 were included (n=1 547 818). We excluded individuals with a CHD diagnosis prior to 2008 (n=67 619), individuals without workplace information (n=576 663), individuals lacking residential address (n=4139) and individuals who had unknown parents (n=7076). A total of 892 321 individuals were thus included in the study (426 440 men and 465 881 women). PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome variable was incident CHD during follow-up between 2008 and 2012. The association between educationwork and neighbourhood SESwork and the outcome was explored using multilevel and cross-classified logistic regression models to determine ORs and 95% CIs, with individuals nested within workplaces and neighbourhoods. All models were conducted in both men and women and were adjusted for age, income, marital status, educational attainment and neighbourhood SESresidence. RESULTS: Low (vs high) educationwork was significantly associated with increased CHD incidence for both men (OR 1.29, 95% CI 1.23 to 1.34) and women (OR 1.38, 95% CI 1.29 to 1.47) and remained significant after adjusting for potential confounders. These findings were not replicable for the variable neighbourhood SESwork. CONCLUSIONS: Workplace socioeconomic characteristics, that is, the educational attainment of an individual's colleagues, may influence CHD risk, which represents new knowledge relevant to occupational health management at workplaces.

The relation of body mass index, body height, and parity to pyelonephritis: A nationwide population-based cohort study of over one million parous women (1997-2018).

OBJECTIVES: We aimed to explore the association between various physiological factors and pyelonephritis in parous women. METHODS: Swedish nationwide registers were used to identify 1,073,467 parous women aged 15-50 years. The study period began in 1997 and ended in 2018, or at the first incidence of pyelonephritis, death, or emigration. Cox proportional hazards methods were used to determine hazard ratios (HRs) and 95% confidence intervals (CIs) of pyelonephritis in relation to body mass index (BMI) and body height adjusted for age, parity, and individual-level sociodemographic variables. RESULTS: A total of 21,625 women (2.0%) were diagnosed with pyelonephritis during follow-up. In the fully adjusted model, low BMI (<18.5) was associated with pyelonephritis (HR 1.13, 95% CI 1.06-1.21). Parity and certain sociodemographic characteristics were also independently associated with pyelonephritis. Body height <161 cm was associated with pyelonephritis (HR 1.12, 95% CI 1.09-1.16) in all but the fully adjusted model. CONCLUSION: Low BMI and body height seem to be associated with uncomplicated pyelonephritis. More research is needed to verify these findings and identify possible mechanisms.

Association Between Neighborhood Deprivation and Heart Failure Among Patients With Diabetes Mellitus: A 10-Year Follow-Up Study in Sweden.

BACKGROUND: Our aim was to study the potential effect of neighborhood deprivation on incident heart failure (HF) in patients with diabetes mellitus (DM). METHODS: The study population included adults (n = 434,542) aged 30 years or older with DM followed from 2005 to 2015 in Sweden for incident HF. The association between neighborhood deprivation and the outcome was explored using Cox regression analysis, with hazard ratios (HRs) and 95% confidence intervals (95% CIs). All models were conducted in both men and women and adjusted for age, educational level, family income, employment status, region of residence, immigrant status, marital status, mobility, and comorbidities. DM patients living in neighborhoods with high or moderate levels of deprivation were compared with those living in neighborhoods with low deprivation scores (reference group). RESULTS: There was an association between level of neighborhood deprivation and HF in DM patients. The HRs were 1.27, 95% CI 1.21-1.33, for men and 1.30, 95% CI 1.23-1.37, for women) among DM patients living in high deprivation neighborhoods compared with those from low deprivation neighborhoods. After adjustments for potential confounders, the higher HRs of HF remained significant: 1.11, 95% CI 1.06-1.16, in men and 1.15, 95% CI 1.09-1.21, in women living in high deprivation neighborhoods. CONCLUSIONS: Increased incidence rates of HF among DM patients living in deprived neighborhoods raise important clinical and public health concerns. These findings could serve as an aid to policy-makers when allocating resources in primary health-care settings as well as to clinicians who encounter patients in deprived neighborhoods.

Causal nature of neighborhood deprivation on individual risk of coronary heart disease or ischemic stroke: A prospective national Swedish co-relative control study in men and women.

We studied the association between neighborhood socioeconomic status (SES) and incidence of coronary heart disease (CHD) or ischemic stroke in the total population and in full- and half-siblings to determine whether these associations are causal or a result from familial confounding. Data were retrieved from nationwide Swedish registers containing individual clinical data linked to neighborhood of residence. After adjustment for individual SES, the association between neighborhood SES and CHD showed no decrease with increasing genetic resemblance, particularly in women. This indicates that the association between neighborhood SES and CHD incidence is partially causal among women, which represents a novel finding.

Neighborhood socioeconomic characteristics and statin medication in patients with myocardial infarction: a Swedish nationwide follow-up study.

BACKGROUND: Coronary heart disease (CHD) and myocardial infarction (MI) are associated with neighborhood-level socioeconomic status (SES). Statins are important drugs for secondary prevention of MI. However, no study has determined whether neighborhood-level SES is associated with statin medication in MI patients. We aimed to determine whether there is a difference in statin medication rate in MI patients across different levels of neighborhood SES. METHODS: All patients in Sweden, diagnosed with incident MI from January 1st, 2000 until December 31(st) 2010, were followed (n = 116,840). Of these, 89.7 % received statin medication. Data were analyzed by multilevel logistic regression, with individual-level characteristics (age, marital status, family income, educational attainment, country of origin, urban/rural status and comorbidities/chronic conditions related to MI) as covariates. RESULTS: Low neighborhood-level SES was significantly associated with low statin medication rate (Odds Ratio 0.80). In the full model, which took into account individual-level socioeconomic characteristics and MI comorbidities, the odds no longer remained significant. CONCLUSIONS: Individual-level approaches may be most important in health care policies regarding statin medication in MI patients.

Negative autoregulation matches production and demand in synthetic transcriptional networks.

We propose a negative feedback architecture that regulates activity of artificial genes, or "genelets", to meet their output downstream demand, achieving robustness with respect to uncertain open-loop output production rates. In particular, we consider the case where the outputs of two genelets interact to form a single assembled product. We show with analysis and experiments that negative autoregulation matches the production and demand of the outputs: the magnitude of the regulatory signal is proportional to the "error" between the circuit output concentration and its actual demand. This two-device system is experimentally implemented using in vitro transcriptional networks, where reactions are systematically designed by optimizing nucleic acid sequences with publicly available software packages. We build a predictive ordinary differential equation (ODE) model that captures the dynamics of the system and can be used to numerically assess the scalability of this architecture to larger sets of interconnected genes. Finally, with numerical simulations we contrast our negative autoregulation scheme with a cross-activation architecture, which is less scalable and results in slower response times.