Workplace Addresses Research Articles

Associations of takeaway outlets with takeaway food consumption and adiposity: longitudinal analysis of the Fenland cohort.

This study builds on prior findings that link increased availability of takeaway food outlets in home, workplace, and commuting environments to greater takeaway consumption and adiposity. Using longitudinal data, we examine associations of takeaway availability at baseline with changes in consumption and adiposity between baseline and follow-up. We analyzed data from the Fenland Study, with baseline data from 2005 to 2015 and follow-up from 2015 to 2020. Takeaway outlet availability within 1 mile of participants' home and workplace addresses, based on 2011 local authority data, was assessed. Outcomes included takeaway food consumption (from a food frequency questionnaire) and body fat percentage (measured via dual-energy x-ray absorptiometry) at follow-up. Among 7581 participants (mean [SD] age, 49.3 [7.4] years) with a mean follow-up of 6.7 years, no positive association was found between takeaway outlet availability at baseline and changes in consumption or body fat percentage. However, among the 12 associations tested, the highest combined home-workplace availability of takeaway outlets, compared with none, was associated with a 0.68 decrease in body fat percentage (95% CI: 0.24-1.12). Although takeaway outletavailability was linked to greater consumption and adiposity at baseline, it did not predict changes over time, underscoring the complexity of dietary behaviors and their relationship with the neighborhood food environment.

Relationship between exposure to fine particulate matter and cardiovascular risk factors and the modifying effect of socioeconomic status: a cross-sectional study in Beijing, China.

Accumulating research suggested that long-term exposure to fine particulate matter (PM2.5) is related to cardiovascular disease (CVD). However, evidence regarding the relationship between PM2.5 and CVD risk factors remains inconsistent. We hypothesized that this association may be partially modified by socioeconomic status (SES). To investigate the relationships and to test the modifying effect of SES, we included baseline data for 21,018 adults from September 2017 to May 2018. PM2.5 concentrations were determined by employing an amalgamation of linear measurements obtained from monitoring stations located near the participants' residential and workplace addresses. We assessed SES across several domains, including income, education, and occupation levels, as well as through a composite SES index. The results indicated that for every 10 μg/m3 increase in PM2.5 exposure, the risk of hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and hyperhomocysteinemia (HHcy) increased by 7.7% [Odds ratio (OR) = 1.077, 95% Confidence Interval (CI) = 1.011, 1.146], 19.6% (OR = 1.196, 95% CI = 1.091, 1.312), 4.2% (OR = 1.042, 95% CI = 1.002, 1.084), and 17.1% (OR = 1.171, 95% CI = 1.133, 1.209), respectively. Compared to the high SES group, those with low SES are more prone to hypercholesterolemia, hyperbetalipoproteinemia, diabetes, and HHcy. Notably, the disparities in SES appear significant in the relationship between PM2.5 exposure and hypercholesterolemia as well as hyperbetalipoproteinemia. But for diabetes and HHcy, the modification effect of SES on PM2.5 shows an inconsistent pattern. In conclusion, the results confirm the association between PM2.5 and cardiovascular risk factors and low SES significantly amplified the adverse PM2.5 effect on dyslipidemia. It is crucial to emphasize a need to improve the socioeconomic inequality among adults in Beijing and contribute to the understanding of the urgency in protecting the health of vulnerable groups.

Exposure to low levels of hydrogen sulphide and its impact on chronic obstructive pulmonary disease and lung function in the geothermal area of Mt. Amiata in Italy: The cross-sectional InVETTA study.

The geothermal power plants for electricity production currently active in Italy are all located in Mt. Amiata area in the Tuscany region. A cross-sectional survey was conducted in the framework of the regional project "InVETTA-Biomonitoring Survey and Epidemiological Evaluations for the Protection of Health in the Amiata Territories", using objective measures of lung function to investigate the role of hydrogen sulphide (H2S) in affecting the respiratory health of the population living in this area. 2018 adults aged 18-70 were enrolled during 2017-2019. Home and workplace addresses of participants were geocoded. Dispersion modelling was used to evaluate the spatial variability of exposure to H2S from the geothermal power plants' emissions. We estimated average long-term historical exposure to H2S and more recent exposure indicators. Chronic Obstructive Pulmonary Disease (COPD) was defined according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD). Multivariable logistic regressions were performed to investigate associations between outcome and exposure. Our findings did not showed any evidence of an association between increasing H2S exposure and lung function impairments. Some risk reductions were observed: a -32.8% (p = 0.003) for FEV1<80% and a -51.7% (p = 0.001) risk decrease for FVC<80% were associated with interquartile increase (13.8 μg/m3) of H2S levels. Our study provides no evidence that chronic exposure to low levels of H2S is associated with decrements in pulmonary function, suggesting that ambient H2S exposure may benefit lung function.

Examining the geographical distribution of air pollution disparities across different racial and ethnic groups: Incorporating workplace addresses

BackgroundMost previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration. MethodIn the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM2.5, NO2, O3), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data. ResultsWe found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants. ConclusionsThe results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO2. Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure.

Effects of walkability on physical activity and obesity: a prospective observational study protocol

IntroductionThe prevalence of overweight and obesity is increasing worldwide, which could lead to a set of chronic and metabolic diseases. Physical activity is a modifiable factor for obesity, which was...

Utility of Spatial Point-Pattern Analysis Using Residential and Workplace Geospatial Information to Localize Potential Outbreak Sources.

Identifying the source of an outbreak facilitates its control. Spatial methods are not optimally used in outbreak investigation, due to a mix of the complexities involved (e.g., methods requiring additional parameter selection), imperfect performance, and lack of confidence in existing options. We simulated 30 mock outbreaks and compared 5 simple methods that do not require parameter selection but could select between mock cases’ residential and workplace addresses to localize the source. Each category of site had a unique spatial distribution; residential and workplace address were visually and statistically clustered around the residential neighborhood and city center sites respectively, suggesting that the value of workplace addresses is tied to the location where an outbreak might originate. A modification to centrographic statistics that we propose—the center of minimum geometric distance with address selection—was able to localize the mock outbreak source to within a 500 m radius in almost all instances when using workplace in combination with residential addresses. In the sensitivity analysis, when given sufficient workplace data, the method performed well in various scenarios with only 10 cases. It was also successful when applied to past outbreaks, except for a multisite outbreak from a common food supplier.

A weekly time-weighted method of outdoor and indoor individual exposure to particulate air pollution

The aim of this study was to estimate the weekly time-weighted (outdoor and indoor activity patterns) individual exposure to particulate air pollutants (PM10, PM2.5 and PM1) of pregnant women. A total of 4928 pregnancy women were recruited during their early pregnancy, and 4278 (86.8%) were successfully followed-up at childbirth. Each individual weekly average PM10 and PM2.5 concentrations at the residential and workplace addresses from three months before pregnancy to childbirth was estimated using a spatiotemporal land use regression (ST-LUR) model, and the weekly PM1 concentration was estimated employing a generalized additive model (GAM) which utilized weekly PM2.5 and meteorological factors as independent predictors. Then, the time-weighted individual exposure to particulate air pollutants during workdays and non-workdays during the period from three months before pregnancy to childbirth was estimated based on the estimated weekly air pollutant concentrations and each participant’s indoor and outdoor activity model, respectively. Data analysis was carried out by R software (version 3.5.1) and packages “SpatioTemporal”, “mgcv” and “splines” were mainly used. This method takes a full consideration of indoor and outdoor activity patterns in the individual exposure to particulate air pollutants.•A ST-LUR model was used to estimate the individual weekly average PM10 and PM2.5 concentrations at their residential and workplace addresses.•A GAM was applied to estimate the weekly average PM1 concentration at individual residential and workplace addresses.•Individual weekly exposure to particulate air pollutants during workdays and non-workdays was assessed based on the estimated particulate air pollutant concentrations and their indoor and outdoor activity model.

Impacts of Personal Mobility and Diurnal Concentration Variability on Exposure Misclassification to Ambient Pollutants.

Appreciating the uncertainty margins of exposure assessment to air pollution requires good understanding of its variability throughout the daily activities. This study describes a modeling framework for estimating exposure to air pollutants for a representative sample of working Israeli adults ( N ∼ 168 000) for which both the residence and workplace addresses were available. Individual daily trajectories were simulated by accounting for five generic daily activities: at home, at work, while in commute from home to work and back, and during out-of-home leisure activities. The integrated daily exposure to nitrogen dioxide (NO2) was estimated for each individual by tracking the daily trajectory through an NO2 concentration map, obtained using a dynamic and highly resolved dispersion-like model (temporal resolution, half-hourly; spatial resolution, 500 m). Accounting for the subjects' daily mobility was found to affect their exposure more significantly than accounting solely for the diurnal concentration variability, yet a synergistic effect was noted when accounting for both factors simultaneously. Exposure misclassification varies along the day, with the work microenvironment found to contribute the most to it. In particular, regardless of the high concentrations encountered during the commute, their contribution to the integrated daily exposure is small due to the relatively short time spent in this activity by most people.

Impacts of geocoding uncertainty on reconstructed PFOA exposures and their epidemiological association with preeclampsia

Many epidemiology studies have investigated associations of perfluorooctanoate (PFOA) exposures with a variety of adverse health outcomes for participants in the C8 Health Project. The exposure concentrations (i.e., air and groundwater) used in these studies were determined primarily based on participant’s residential locations. However, for residential addresses that could not be geocoded to the street level, the exposure concentrations were assigned based on population-weighted ZIP code centroid, which may result in exposure mischaracterization. The aim of this current study is to evaluate the potential impact of mischaracterized exposure concentrations due to geocoding uncertainty on the predicted serum PFOA concentrations and the epidemiological association between PFOA exposure and preeclampsia. For both workplace addresses and incompletely geocoded residential addresses, we used Monte Carlo (MC) simulation to assign alternate geographic locations within the reported ZIP code (instead of population-weighted ZIP code centroids) and the corresponding exposure concentrations. We found that mischaracterization of residential exposure due to population-weighted ZIP code centroid assignment had no significant impact on the serum PFOA concentration predictions and the epidemiological association of PFOA exposure with preeclampsia. In contrast, the uncertainty in workplace exposure moderately impacted the rank exposure among the participants. We observed a 41% increase in the average adjusted odds ratio of preeclampsia occurrence that may be due to differing proportions of cases (64.3%) and controls (54.5%) with workplace address geocodes during pregnancy. This finding suggests that differential exposure mischaracterization can be reduced by obtaining accurate exposure information such as street addresses and tap water consumption, for both workplaces and residences. The analysis we present is one approach for estimating the potential impacts of positional errors in a geocoding-based exposure assessment on exposure estimates and epidemiological study results.

Commuting behaviors and exposure to air pollution in Montreal, Canada

BackgroundVehicular traffic is a major source of outdoor air pollution in urban areas, and studies have shown that air pollution is worse during hours of commuting to and from work and school. However, it is unclear to what extent different commuting behaviors are a source of air pollution compared to non-commuters, and if air pollution exposure actually differs by the mode of commuting. This study aimed to examine the relationships between commuting behaviors and air pollution exposure levels measured by urinary 1-OHP (1-hydroxypyrene), a biomarker of exposure to polycyclic aromatic hydrocarbons (PAHs). MethodsA cross-sectional study of 174 volunteers living in Montreal, 92 females and 82 males, aged 20 to 53years was conducted in 2011. Each participant completed a questionnaire regarding demographic factors, commuting behaviors, home and workplace addresses, and potential sources of PAH exposure, and provided a complete first morning void urine sample for 1-OHP analysis. Multivariable general linear regression models were used to examine the relationships between different types of commuting and urinary 1-OHP levels. ResultsCompared to non-commuters, commuters traveling by foot or bicycle and by car or truck had a significantly higher urinary 1-OHP concentration in urine (p=0.01 for foot or bicycle vs. non-commuters; p=0.02 for car or truck vs. non-commuters); those traveling with public transportation and combinations of two or more types of modes tended to have an increased 1-OHP level in urine (p=0.06 for public transportation vs. non-commuters; p=0.05 for commuters with combinations of two or more types of modes vs. non-commuters). No significant difference in urinary 1-OHP variation was found by mode of commuting. ConclusionThis preliminary study suggests that despite the mode of commuting, all types of commuting during rush hours increase exposure to air pollution as measured by a sensitive PAH metabolite biomarker, and mode of commuting did not explain exposure variation.

Pesticides that inhibit the ubiquitin–proteasome system: Effect measure modification by genetic variation in SKP1 in Parkinson׳s disease

Cytoplasmic inclusions known as Lewy bodies, a hallmark of Parkinson′s disease (PD) pathology, may protect against cytotoxic proteins. Since the ubiquitin–proteasome system (UPS) degrades cytotoxic proteins, dysfunction in the UPS may contribute to PD etiology. Our goal in this study was to screen pesticides for proteasome inhibition and investigate (i) whether ambient exposures to pesticides that inhibit the UPS increase PD risk and (ii) whether genetic variation in candidate genes of the UPS pathway modify those increased risks. We assessed 26S UPS activity in SK-N-MCu cells by fluorescence. We recruited idiopathic PD cases (n=360) and population-based controls (n=816) from three counties in California with considerable commercial agriculture. We determined ambient pesticide exposure by our validated GIS-based model utilizing residential and workplace address histories. We limited effect measure modification assessment to Caucasians (287 cases, 453 controls). Eleven of 28 pesticides we screened inhibited 26S UPS activity at 10µM. Benomyl, cyanazine, dieldrin, endosulfan, metam, propargite, triflumizole, and ziram were associated with increased PD risk. We estimated an odds ratio of 2.14 (95% CI: 1.42, 3.22) for subjects with ambient exposure to any UPS-inhibiting pesticide at both residential and workplace addresses; this association was modified by genetic variation in the s-phase kinase-associated protein 1 gene (SKP1; interaction p-value=0.005). Our results provide evidence that UPS-inhibiting pesticides play a role in the etiology of PD and suggest that genetic variation in candidate genes involved in the UPS pathway might exacerbate the toxic effects of pesticide exposures.

Functional paraoxonase 1 variants modify the risk of Parkinson's disease due to organophosphate exposure

BackgroundWe previously demonstrated that carriers of the “slower metabolizer” MM genotype of paraoxonase (PON1) who were also exposed to ambient organophosphate (OP) pesticides at their residences were at increased risk of developing Parkinson's disease (PD). Here, with a larger sample size, we extend our previous investigation to consider additional sources of ambient exposure and examined two additional functional PON1 variants. MethodsFrom 2001 to 2011, we enrolled incident cases of idiopathic PD and population controls living in central California. We genotyped three well-known functional PON1 SNPs: two exonic polymorphisms (PON1L55M and PON1Q192R) and the promoter region variant (PON1C-108T). Ambient exposures to diazinon, chlorpyrifos, and parathion at residential and workplace addresses were assessed using a validated geographic information system-based model incorporating records of agricultural pesticide applications in California. ResultsThe odds ratio (OR) for Caucasians exposed to OPs at either residential or workplace addresses varied by PON1 genotype; for exposed carriers of the “faster” metabolizer genotypes, ML or LL, we estimated lower odds ratios (range, 1.20–1.39) than for exposed carriers of the “slower” metabolizer genotype MM (range, 1.78–2.45) relative to unexposed carriers of the faster genotypes. We observed similarly increased ORs for exposure across PON1Q192R genotypes, but no differences across PON1C-108T genotypes. The largest ORs were estimated for exposed carriers of both PON1192QQ and PON155MM (OR range, 2.84–3.57). ConclusionsSeveral functional PON1 variants may act together to modify PD risk for ambient OP exposures. While either PON1L55M or PON1Q192R may be sufficient to identify increased susceptibility, carriers of both slow metabolizer variants seem most susceptible to OP exposures.

Adult asthma and traffic exposure at residential address, workplace address, and self-reported daily time outdoor in traffic: A two-stage case-control study

BackgroundMost epidemiologic studies use traffic at residential address as a surrogate for total traffic exposure when investigating effects of traffic on respiratory health. This study used GIS (Geographical Information Systems) to estimate traffic exposure, not only on residential, but also on workplace address, in addition to survey questions on time spent in traffic during commuting or other daily activities.The aim was to investigate 1) if there is an association between traffic exposure and prevalence of adult asthma and asthma symptoms, and 2) if so, does this association become stronger using more complete traffic exposure information.MethodsThis study was conducted in two stages: A first cross-sectional survey in Southern Sweden 2004 (n = 24819, 18-80 years, response rate 59%) was followed by a case-control study in 2005 to obtain more detailed exposure and confounder information (n = 2856, asthmatics and controls (1:3), 86% response rate). In the first survey, only residential address was known. In the second survey, questions about workplace addresses and daily time spent in traffic were also included. Residential and workplace addresses were geocoded and linked with GIS to road data and dispersion modelled outdoor concentrations of NOx (annual mean, 250 × 250 m resolution).ResultsLiving within 50 m of a road (measured by GIS) with traffic intensity of >10 cars/minute (compared with no road within this distance) was associated with an increased prevalence of asthma, (OR = 1.8, 95% CI = (1.1-2.8), and with asthma symptoms last 12 months. No statistically significant effects were seen for traffic exposure at workplace address, daily time spent in traffic, or commuting time to work, after adjustment for confounders. A combined total exposure estimate did not give a stronger association with asthma prevalence or asthma symptoms.ConclusionsTraffic exposure at close proximity to residential address showed association with asthma prevalence and asthma symptoms last 12 months, among adults in southern Sweden. The associations were not stronger when accounting for total traffic exposure. This could reflect exposure misclassfication at workplace address and for other daily time in traffic, but also that residential address remains the main determinant for traffic exposure among adults.

Methods for determining route distances in active commuting – Their validity and reproducibility

Distance is a variable of pivotal importance in transport studies. Therefore, after checking the validity of a potential criterion method for measuring active commuting route distances, this method was used to assess the validity and reproducibility of four methods of approximating the commuting route distances covered by pedestrians and bicyclists. The methods assessed were: self-estimated distance, straight-line distance, GIS shortest-route distance, and GPS-measured distance. For this purpose, participants were recruited when walking or bicycling in Stockholm, Sweden. Questionnaires and individually-adjusted maps were sent twice to 133 participants. The distances of map-drawn commuting routes functioned as criterion distances. The participants were also asked to estimate their distances. The straight-line distance between origin and destination was measured using map-drawn routes. The shortest route between home addresses and workplace addresses was calculated with three GIS algorithms. Eighty-six trips were measured with GPS. The main results were that test–retest intraclass correlation coefficients (ICC) exceeded 0.99 for all methods, except for self-estimated distance (ICC = 0.76). No order effects existed between test and retest. Significant differences were, however, noted between criterion distance and self-estimated distance (114 ± 63%), straight-line distance (79.1 ± 10.5%), GIS shortest route (112 ± 18% to 121 ± 22%) and GPS distance (105 ± 4%). We conclude that commonly-used distance estimation methods produce systematic errors of differing magnitudes when used in a context of active commuting in suburban and urban environments. These errors can at average level be corrected for, whereas individual relative errors will remain.

A Contract‐Based Training System for Rural Physicians: Follow‐Up of Jichi Medical University Graduates (1978‐2006)

The number of studies on long-term effects of rural medical education programs is limited. Personal factors that are associated with long-term retention of physicians in rural areas are scarcely known. The authors studied the outcomes of Jichi Medical University (JMU), whose mission is to produce rural doctors, and analyzed the characteristics of its graduates who engaged in rural practice even after their 9-year obligation of rural practice. A retrospective cohort study was conducted including 2,988 JMU students who graduated between 1978 and 2006. Baseline data were collected at matriculation and graduation. Workplace addresses were surveyed in 2000, 2004, and 2006. Follow-up rates were 98.7%, 98.2%, and 98.0% respectively. After their obligation period, JMU graduates were 4 times more likely than non-JMU graduates to work in rural areas. The higher proportion of JMU graduates in rural areas did not change significantly between 1994 and 2004. The rural recruitment rate of post-obligation JMU graduates was somewhat lower than rates reported for top rural medical education programs in the United States. In multivariate analyses, rural upbringing and primary care specialty were positively associated with having a rural address in at least one post-obligation study year (OR 1.89 [95% CI 1.27-2.81]; and 7.63 [4.37-13.34], respectively) and settlement (ie, having a rural address over multiple years) after the contract (1.90 [1.04-3.48]; and 32.07 [4.43-232.24], respectively). Graduation from a private high school had a negative association with recruitment (0.56 [0.33-0.96]). JMU was successful in increasing the number and retention of rural physicians. Rural origin and primary care specialty have a positive impact on both recruitment and retention after the rural obligation.

Long-term effect of the Home Prefecture Recruiting Scheme of Jichi Medical University, Japan

Jichi Medical University (JMU) is an experimental medical school established in 1972 by the Japanese Ministry of Home Affairs and all 47 prefectures in Japan (equivalent to the states of Australia) with a special mission to produce rural doctors and distribute them nationwide. The JMU has adopted a contract-based 'home prefecture recruiting scheme' in which students recruited evenly from all the 47 prefectures of Japan are required to work in their home prefectures for 9 years (including 6 years of rural service) after graduation in exchange for having their 6 years of undergraduate medical education tuition fees waived. Although the JMU system is now being partially adopted by an increasing number of other medical schools in Japan, the effectiveness of this equal distribution scheme is largely unknown. A retrospective cohort study of 1255 graduates who had completed their contract by 2000 was conducted. Baseline data were collected at matriculation and graduation between 1972 and 1991. Workplace addresses were followed up in 2000, 2004, and 2006. Follow-up rates were 98.7% in 2000, 98.2% in 2004, and 98.0% in 2006. Data excerpted from the 2004 National Population Census including various demographic indicators (eg population, population density, and physicians/population ratio) for each of the 47 prefectures were merged, through prefectural identification codes, with the baseline and follow-up addresses of the subjects. Of all JMU graduates after contract, 69.8% settled in their home prefectures. The rates varied from 45.5% to 93.3% among the prefectures (p<0.001). The settlement rate tended to be higher in prefectures with a lower population density or physician : population ratio. Among prefectural demographics, the physician : population ratio and medical institution : population ratio were negatively correlated with settlement rate in the prefecture (correlation coefficient -0.34 [p=0.020]; and -0.35 [p=0.017], respectively). In short, prefectures with a relative shortage of physicians had higher settlement rates. In multivariable analysis of personal factors, female sex and physician : population ratio of home prefecture were negatively associated with settlement (OR 0.25 [95%CI 0.10-0.58] and OR for 1 SD increase 0.82 [0.71-0.94], respectively). Primary care specialty was positively associated with settlement (1.80 [1.35-2.39]). Mother's higher academic background was negatively associated with settlement (OR for university vs junior high school graduate 0.54 [95%CI 0.34-0.88]). The home prefecture recruiting scheme has attained its goal, particularly in medically underserved prefectures. The high retention rates indicate that the scheme would be beneficial for other medical schools in Japan, which are now beginning to implement programs similar to JMU, and also medical educators and policy makers in countries searching for effective political interventions to maldistribution of physicians.

Characteristics of medical students with rural origin: Implications for selective admission policies

Selective admission policies of medical schools favoring students of rural origin have been implemented in many countries in hope of increasing rural physicians. This study evaluated the characteristics of medical students from rural origins and their choice of future practice location. Personal, familial, and academic information of 1929 graduates of Jichi Medical University (JMU), a Japanese medical school with a special mission to produce rural doctors, was collected on admission and graduation between 1972 and 1997, and follow-up information on workplace addresses were collected in 2000, 2004, and 2006. Jichi Medical University has a unique contract system under which all the graduates have the obligation to work in rural areas in exchange for having their tuition fee during their 6 years of undergraduate medical education waived. Subjects with rural origin were more likely to have parents with lower academic background, improve their academic standing throughout undergraduate medical education, and engage in rural practice than those from urban origins. Positive linear relationships between places of upbringing and workplaces were recognized in various geographic/demographic indicators. The selective admission policy seems to be a reasonable way of increasing the number of rural physicians without placing an undue burden on medical schools.