Primary care, social inequalities, and all-cause, heart disease, and cancer mortality in US counties, 1990

OBJECTIVES: We tested the association between the availability of primary care and income inequality on several categories of mortality in US counties. METHODS: We used cross-sectional analysis of data from counties (n=3081) in 1990, including analysis of variance and multivariate ordinary least squares regression. Independent variables included primary care resources, income inequality, and sociodemographics. RESULTS: Counties with higher availability of primary care resources experienced between 2% and 3% lower mortality than counties with less primary care. Counties with high income inequality experienced between 11% and 13% higher mortality than counties with less inequality. CONCLUSIONS: Primary care resources may partially moderate the effects of income inequality on health outcomes at the county level.     

Quantifying the health benefits of primary care physician supply in the United States.

This analysis addresses the question, Would increasing the number of primary care physicians improve health outcomes in the United States? A search of the PubMed database for articles containing "primary care physician supply" or "primary care supply" in the title, published between 1985 and 2005, identified 17 studies, and 10 met all inclusion criteria. Results were reanalyzed to assess primary care effect size and the predicted effect on health outcomes of a one-unit increase in primary care physicians per 10,000 population. Primary care physician supply was associated with improved health outcomes, including all-cause, cancer, heart disease, stroke, and infant mortality; low birth weight; life expectancy; and self-rated health. This relationship held regardless of the year (1980-1995) or level of analysis (state, county, metropolitan statistical area (MSA), and non-MSA levels). Pooled results for all-cause mortality suggest that an increase of one primary care physician per 10,000 population was associated with an average mortality reduction of 5.3 percent, or 49 per 100,000 per year.     

The relationship between primary care, income inequality, and mortality in US States, 1980-1995

OBJECTIVES: This study tests the robustness of the relationships between primary care, income inequality, and population health by (1) assessing the relationship during 4 time periods-1980, 1985, 1990 and 1995; (2) examining the independent effect of components of the primary care physician supply; (3) using 2 different measures of income inequality (Robin Hood index and Gini coefficient); and (4) testing the robustness of the association by using 5-year time-lagged independent variables. DATA SOURCES/STUDY SETTING: Data are derived from the Compressed Mortality Files, the US Department of Commerce and the Census Bureau, the National Center for Health Statistics, the Centers for Disease Control and Prevention, and the American Medical Association Physician Master File. The unit of analysis was the 50 US states over a 15-year period. STUDY DESIGN: Ecological, cross-sectional design for 4 selected years (1980, 1985, 1990, 1995), and incorporating 5-year time-lagged independent variables. The main outcome measure is age-standardized, all-cause mortality per 100,000 population in all 50 US states in all 4 time periods. DATA COLLECTION/EXTRACTION METHODS: The study used secondary data from publicly available data sets. The CDC WONDER/PC software was used to obtain mortality data and directly standardize them for age to the 1980 US population. Data used to calculate the income inequality measure came from the US census population and housing summary tapes for the years 1980 to 1995. Counts of the number of households that fell into each income interval along with the total aggregate income and the median household income were obtained for each state. The Gini coefficient for each state was calculated using software developed for this purpose. RESULTS: In weighted multivariate regressions, both contemporaneous and time-lagged income inequality measures (Gini coefficient, Robin Hood Index) were significantly associated with all-cause mortality (P <.05 for both measures for all time periods). Contemporaneous and time-lagged primary care physician-to-population ratios were significantly associated with lower all-cause mortality (P <.05 for all 4 time periods), whereas specialty care measures were associated with higher mortality (P <.05 for all time periods, except 1990, where P <.1). Among primary care subspecialties, only family medicine was consistently associated with lower mortality (P <.01 for all time periods). CONCLUSIONS: Enhancing primary care, particularly family medicine, even in states with high levels of income inequality, could lead to lower all-cause mortality in those states.     

Erratum to: Racial Segregation,Income Inequality,and Mortality in US Metropolitan Areas

Evidence of the association between income inequality and mortality has been mixed. Studies indicate that growing income inequalities reflect inequalities between, rather than within, racial groups. Racial segregation may play a role. We examine the role of racial segregation on the relationship between income inequality and mortality in a cross-section of US metropolitan areas. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10% black (N = 107). Deaths for the time period 1991–1999 were used to calculate age-adjusted all-cause mortality rates for each metropolitan statistical area (MSA) using direct age-adjustment techniques. Multivariate least squares regression was used to examine associations for the total sample and for blacks and whites separately. Income inequality was associated with lower mortality rates among whites and higher mortality rates among blacks. There was a significant interaction between income inequality and racial segregation. A significant graded inverse income inequality/mortality association was found for MSAs with higher versus lower levels of black–white racial segregation. Effects were stronger among whites than among blacks. A positive income inequality/mortality association was found in MSAs with higher versus lower levels of Hispanic–white segregation. Uncertainty regarding the income inequality/mortality association found in previous studies may be related to the omission of important variables such as racial segregation that modify associations differently between groups. Research is needed to further elucidate the risk and protective effects of racial segregation across groups.     

Racial Segregation,Income Inequality,and Mortality in US Metropolitan Areas

Evidence of the association between income inequality and mortality has been mixed. Studies indicate that growing income inequalities reflect inequalities between, rather than within, racial groups. Racial segregation may play a role. We examine the role of racial segregation on the relationship between income inequality and mortality in a cross-section of US metropolitan areas. Metropolitan areas were included if they had a population of at least 100,000 and were at least 10% black (N = 107). Deaths for the time period 1991–1999 were used to calculate age-adjusted all-cause mortality rates for each metropolitan statistical area (MSA) using direct age-adjustment techniques. Multivariate least squares regression was used to examine associations for the total sample and for blacks and whites separately. Income inequality was associated with lower mortality rates among whites and higher mortality rates among blacks. There was a significant interaction between income inequality and racial segregation. A significant graded inverse income inequality/mortality association was found for MSAs with higher versus lower levels of black–white racial segregation. Effects were stronger among whites than among blacks. A positive income inequality/mortality association was found in MSAs with higher versus lower levels of Hispanic–white segregation. Uncertainty regarding the income inequality/mortality association found in previous studies may be related to the omission of important variables such as racial segregation that modify associations differently between groups. Research is needed to further elucidate the risk and protective effects of racial segregation across groups.     

Primary care, race, and mortality in US states

This study used US state-level data from 1985 to 1995 to examine the relationship of primary care resources and income inequality with all-cause mortality within the entire population, and in black and white populations. The study is a pooled ecological design with repeated measures using 11 years of state-level data (n=549). Analyses controlled for socioeconomic and demographic characteristics. Contemporaneous and time-lagged covariates were modeled, and all analyses were stratified by race/ethnicity. In all models, primary care was associated with lower mortality. An increase of one primary care doctor per 10,000 population was associated with a reduction of 14.4 deaths per 100,000. The magnitude of primary care coefficients was higher for black mortality than for white mortality. Income inequality was not associated with mortality after controlling for state-level sociodemographic covariates. The study provides evidence that primary care resources are associated with population health and could aid in reducing socioeconomic disparities in health.     

Insulin-like growth factors and subsequent risk of mortality in the United States

Although numerous studies have explored the relation of insulin-like growth factor (IGF)-I and IGF-binding protein (BP) 3 with cancer and cardiovascular disease, only two previous studies are known to have looked at the association of IGF-I and IGF-BP3 with risk of mortality. The objective of this US study was to examine the risk of all-cause, heart disease, and cancer mortality associated with IGF-I and IGF-BP3 levels using data from the Third National Health and Nutrition Examination Survey (NHANES III) and NHANES III Mortality Study (n = 6,061) (1988-2000). The authors constructed proportional hazards models with age as the time scale to determine the association of baseline IGF-I and IGF-BP3 levels with subsequent mortality. After adjustment for baseline measures, there was no increased risk of all-cause, heart disease, or cancer mortality for the lower quartiles of IGF-I compared with the highest quartile. The adjusted relative hazard of all-cause mortality for the lowest quartile of IGF-BP3 compared with the highest quartile was 1.57 (95% confidence interval: 0.98, 2.52), and the trend for risk was significant (p = 0.0364), but there was no increased risk of heart disease or cancer mortality. Results suggest that the association of IGF-I and IGF-BP3 with mortality may differ from associations with incidence of disease.     

Income inequality, primary care, and health indicators

BACKGROUND: The significant association of income inequality with a variety of health indicators is receiving increasing attention. There has also been increasing evidence of a link between primary care and improved health status. We examined the joint relationship between income inequality, availability of primary care, and various health indicators to determine whether primary care has an impact on health indicators by modifying the adverse effect of income inequality. METHODS: Our ecologic study used the US states as the units of analysis. In analyzing the data, we looked at the associations among income inequality, primary care, specialty care, smoking, and health indicators, using Pearson's correlation coefficients for intercorrelations and the adjusted multiple regression procedure. To examine the effect of inequality and primary care on health outcome indicators, we conducted path analyses according to a causal model in which inequality affects health both directly and indirectly through its impact on primary care. RESULTS: Our study indicates that both primary care and income inequality exerted a strong and significant direct influence on life expectancy and total mortality (P <.01). Primary care also exerted a significant direct influence on stroke and postneonatal mortality (P <.01). Although levels of smoking are also influential, the effect of income inequality and primary care persists after controlling for smoking. Primary care serves as one pathway through which income inequality influences population-level mortality and at least some other health outcome indicators. CONCLUSIONS: It appears possible that a primary care orientation may, in part, overcome the severe adverse effects on health of income inequalities.     

Cancer mortality, ethnicity, and socioeconomic status: two New York City groups

Cancer mortality rates for 1979-81 among Puerto Ricans and non-Hispanic whites in New York City are analyzed for cancer in six sites. They include cancers of the lung, esophagus, breast, stomach, colon, ovary, and all cancers. New York City health areas were divided into four quartiles representing four levels of income. In general, Puerto Ricans in New York City have lower mortality rates from cancer than non-Hispanic white residents of the city. In comparing cancer mortality by quartile, Puerto Rican males show little variation. Puerto Rican females show their highest mortality rates from breast cancer in the wealthiest quartile, and non-Hispanic white women show highest mortality rates from breast cancer in the poorest quartile. Non-Hispanic white males show mortality rates from lung cancer in the poorest quartile that are distinctly higher than in the more affluent ones. For all groups, with the exception of Puerto Rican males, mortality rates from all cancers increased progressively with decreasing income. Factors influencing differential mortality rates by quartile appear to include tobacco use, alcohol consumption, occupational hazards, fertility, and differential use of health facilities.     

The relationship of physical activity and body weight with all-cause mortality: results from the Puerto Rico Heart Health Program

PURPOSE: To study the relationship of physical activity and obesity with all-cause mortality in Puerto Rican Men.

METHODS: The Puerto Rico Heart Health Program collected physical activity and anthropometric measurements in 9,824 men between 1962 and 1965. After excluding those with known coronary heart disease at baseline, and those who died within the first three years of the study we analyzed the data for the relationship between physical activity and overweight status to all-cause mortality in 9,136 men.We stratified our participants by quartiles of physical activity. Participants were classified into four categories of body weight: underweight (BMI < 18.5), healthy weight (BMI =18.5–24.9), overweight (BMI = 25–29.9), and obese (BMI = 30+).

RESULTS: After adjusting for age, education, smoking status, hypertension status, hypercholesterolemic status, urban/rural residence, and overweight status, physical activity was independently related to all-cause mortality. All-cause mortality was lower in those in quartile 2 (OR = 0.68, CI = 0.58–0.79) than quartile 1 (reference, sedentary group). Mortality among those in quartile 3 and 4 (0.63, CI = 0.54–0.75; and 0.55, CI = 0.46–0.65, respectively) were also significantly lower than those observed in quartile 1, but not significantly lower than those observed in quartile 2. Furthermore, within every category of body weight, those who were most active had significantly lower odds ratio of all-cause mortality.

CONCLUSION: Our findings support the current recommendation that some physical activity is better than none, in protecting against all-cause mortality. The benefits of an active lifestyle are independent of body weight and that overweight and obese Puerto Rican men who are physically active experienced significant reductions in all-cause mortality compared with their sedentary counterparts.     

Income inequality and ischaemic heart disease in Danish men and women

BACKGROUND: It has been hypothesized that areas with an unequal income distribution are less likely to invest in health and more likely to have a social environment that influences the development of ischaemic heart disease (IHD) METHODS: We used pooled data from two cohort studies conducted in Copenhagen to analyse the association between area income inequality and first admission to hospital or death from IHD in women and men while controlling for individual income and other IHD risk factors. A total of 11 685 women and 10 036 men, with initial health examinations between 1964 and 1992, were followed for a median of 13.8 years. Information on median income share at parish and municipality levels was obtained from population registers. RESULTS: During follow-up 1700 men and 1204 women experienced an IHD event. At parish level income share was inversely associated with an increased risk of IHD in men (hazard ratio [HR](most versus least equal quartile) = 0.85 (95% CI: 0.73-0.98). Among women there was no relation between parish income inequality and IHD. Subject's household income was inversely related to IHD, and when this variable was controlled for, the association between income inequality at parish level and IHD in men attenuated slightly. When behavioural and biological risk factors were entered into the Cox model this relation attenuated further. However, some of these risk factors might mediate rather than confound the effect of income inequality. The association between income inequality at municipality level and IHD was insignificant for men, while in women the relation had a curved shape with those living in the least equal areas having the lowest risk. CONCLUSIONS: This study provides no clear evidence for an association between income inequality measured at parish or municipality level and IHD in Danish adults. The associations were weak and varied between different strata and geographical levels.     

The effect of primary care physician supply and income inequality on mortality among blacks and whites in US metropolitan areas

OBJECTIVES: This study assessed whether income inequality and primary care physician supply have a different effect on mortality among Blacks compared with Whites. METHODS: We conducted a multivariate ecologic analysis of 1990 data from 273 US metropolitan areas. RESULTS: Both income inequality and primary care physician supply were significantly associated with White mortality (P < .01). After the inclusion of the socioeconomic status covariates, the effect of income inequality on Black mortality remained significant (P < .01), but the effect of primary care physician supply was no longer significant (P > .10), particularly in areas with high income inequality. CONCLUSIONS: Improvement in population health requires addressing socioeconomic determinants of health, including income inequality and primary care availability and access.     

Zinc, copper, and magnesium and risks for all-cause, cancer, and cardiovascular mortality

BACKGROUND: Experimental data suggest that zinc, copper, and magnesium are involved in carcinogenesis and atherogenesis. Few longitudinal studies have related these minerals to cancer or cardiovascular disease mortality in a population. METHODS: Data from the Paris Prospective Study 2, a cohort of 4035 men age 30-60 years at baseline, were used to assess the association between serum zinc, copper, and magnesium and all-cause, cancer, and cardiovascular disease mortality. Serum mineral values measured at baseline were divided into quartiles and classified into low (1st quartile, referent group), medium (2nd-3rd quartiles), and high (4th quartile) values. During 18-year follow up, 339 deaths occurred, 176 as a result of cancer and 56 of cardiovascular origin. Relative risks (RRs) for each element were inferred using Cox's proportional hazard model after controlling for various potential confounders. RESULTS: High copper values (4th quartile) were associated with a 50% increase in RRs for all-cause deaths (RR = 1.5; 95% confidence interval = 1.1-2.1), a 40% increase for cancer mortality (1.4; 0.9-2.2), and a 30% increase for cardiovascular mortality (1.3; 0.6-2.8) compared with low values (1st quartile). High magnesium values were negatively related to mortality with a 40% decrease in RR for all-cause (0.6; 0.4-0.8) and cardiovascular deaths (0.6; 0.2-1.2) and by 50% for cancer deaths (0.5; 0.3-0.8). Additionally, subjects with a combination of low zinc and high copper values had synergistically increased all-cause (2.6; 1.4-5.0) and cancer (2.7; 1.0-7.3) mortality risks. Similarly, combined low zinc and high magnesium values were associated with decreased all-cause (0.2; 0.1-0.5) and cancer (0.2; 0.1-0.8) mortality risks. CONCLUSIONS: High serum copper, low serum magnesium, and concomitance of low serum zinc with high serum copper or low serum magnesium contribute to an increased mortality risk in middle-aged men.     

Income Inequality and Mortality in US Counties: Does Minority Racial Concentration Matter?

This study examined (1) the relationship between income inequality and mortality among all counties in the contiguous United States to ascertain whether the relationships found for states and metropolitan areas extend to smaller geographic units and (2) the influence of minority racial concentration on the inequality-mortality linkage. METHODS: This county-level ecologic analysis used data from the Compressed Mortality Files and the US Census. Weighted least squares regression models of age-, sex-, and race-adjusted county mortality rates were estimated to examine the additive and interactive effects of income inequality and minority racial concentration. RESULTS: Higher income inequality at the county level was significantly associated with higher total mortality. Higher minority racial concentration also was significantly related to higher mortality and interacted with income inequality. CONCLUSIONS: The relationship between income inequality and mortality is robust for counties in the United States. Minority concentration interacts with income inequality, resulting in higher mortality in counties with low inequality and a high percentage of Blacks than in counties with high inequality and a high percentage of Blacks.     

Mortality,inequality and race in American cities and states

A number of studies have found that mortality rates are positively correlated with income inequality across the cities and states of the US. We argue that this correlation is confounded by the effects of racial composition. Across states and Metropolitan Statistical Areas (MSAs), the fraction of the population that is black is positively correlated with average white incomes, and negatively correlated with average black incomes. Between-group income inequality is therefore higher where the fraction black is higher, as is income inequality in general. Conditional on the fraction black, neither city nor state mortality rates are correlated with income inequality. Mortality rates are higher where the fraction black is higher, not only because of the mechanical effect of higher black mortality rates and lower black incomes, but because white mortality rates are higher in places where the fraction black is higher. This result is present within census regions, and for all age groups and both sexes (except for boys aged 1-9). It is robust to conditioning on income, education, and (in the MSA results) on state fixed effects. Although it remains unclear why white mortality is related to racial composition, the mechanism working through trust that is often proposed to explain the effects of inequality on health is also consistent with the evidence on racial composition and mortality.     

Independent and joint contributions of economic,social and physical environmental characteristics to mortality in the Detroit Metropolitan Area: A study of cumulative effects and pathways

ObjectivePrevious studies have demonstrated associations between race-based residential segregation, neighborhood socioeconomic and physical environmental characteristics, and mortality. Relatively few studies have examined independent and joint effects of these multiple neighborhood characteristics and mortality, including potential mediating pathways. In this study we examine the extent to which associations between race-based residential segregation and all-cause mortality may be explained by multiple socioeconomic indicators and exposure to air pollutants.MethodsDrawing on data from multiple sources, we assessed bivariate associations between race-based residential segregation (operationalized as percent non-Hispanic Black), education (percent with graduate equivalency degree), poverty (percent below poverty), income inequality (GINI coefficient) and air pollution (ambient PM2.5) and age adjusted all-cause, all race mortality (henceforth all cause mortality) at the census tract level in the Detroit Metropolitan Area. We used inequality curves to assess the (in)equitable distribution of economic and environmental characteristics by census tract racial composition. Finally, we used generalized estimating equations (GEE) to examine independent and joint associations among percent NHB, education, income inequality, and air pollution to all-cause mortality, and test for mediating effects.ResultsBivariate associations between racial composition, education, poverty, income inequality, PM2.5 and all-cause mortality were statistically significant. Census tracts with higher concentrations of NHB residents had significantly lower educational attainment, higher poverty, and greater exposure to PM2.5. In multivariate models, education, income inequality and PM2.5 fully attenuated associations between racial composition and all-cause mortality.ConclusionsResults are consistent with the hypothesis that race-based residential segregation is associated with heightened all-cause mortality, and that those effects are mediated by education, income inequality, and exposure to air pollution at the census tract level. Public health and cross-sector interventions to eliminate race-based residential segregation or to eliminate the maldistribution of educational and economic resources, and environmental exposures, across census tracts could substantially reduce regional inequities in all-cause mortality.     

Mortality from heart,respiratory, and kidney disease in coal mining areas of Appalachia

Purpose  The purpose of this study was to test whether population mortality rates from heart, respiratory and kidney disease were higher as a function of levels of Appalachian coal mining after control for other disease risk factors. Methods  The study investigated county-level, age-adjusted mortality rates for the years 2000–2004 for heart, respiratory and kidney disease in relation to tons of coal mined. Four groups of counties were compared: Appalachian counties with more than 4 million tons of coal mined from 2000 to 2004; Appalachian counties with mining at less than 4 million tons, non-Appalachian counties with coal mining, and other non-coal mining counties across the nation. Forms of chronic illness were contrasted with acute illness. Poisson regression models were analyzed separately for male and female mortality rates. Covariates included percent male population, college and high school education rates, poverty rates, race/ethnicity rates, primary care physician supply, rural-urban status, smoking rates and a Southern regional variable. Results  For both males and females, mortality rates in Appalachian counties with the highest level of coal mining were significantly higher relative to non-mining areas for chronic heart, respiratory and kidney disease, but were not higher for acute forms of illness. Higher rates of acute heart and respiratory mortality were found for non-Appalachian coal mining counties. Conclusions  Higher chronic heart, respiratory and kidney disease mortality in coal mining areas may partially reflect environmental exposure to particulate matter or toxic agents present in coal and released in its mining and processing. Differences between Appalachian and non-Appalachian areas may reflect different mining practices, population demographics, or mortality coding variability.     

Cause-specific mortality differences across socioeconomic position of municipalities in Japan, 1973-1977 and 1993-1998: increased importance of injury and suicide in inequality for ages under 75

BACKGROUND: Socioeconomic inequality in health has been a major concern in public health. This study examined socioeconomic inequality in regional mortality and the impact on inequality by cause of deaths in 1973-1977 and 1993-1998 using municipal statistics in Japan. METHODS: The municipalities across the country (N = 3244 in 1973-1977 and 3334 in 1993-1998) were classified into quintiles according to the index of socioeconomic position (SEP) obtained by principal component analysis of municipal indicators related to income and education. Mortality gradient by SEP for selected major causes of death in the population aged 0-74 years was examined using standardized mortality ratio by quintile and rate ratio of mortality across quintiles. As a measure of cause-specific impact on inequality, the number of excess deaths from each cause in the lower four SEP quintiles compared with the highest quintile was calculated. RESULTS: Mortality gradient by SEP and excess deaths in the lower SEP quintiles due to injury and suicide markedly increased from 1973-1977 to 1993-1998 for both males and females. In contrast, stroke, especially cerebral haemorrhage, showed a decrease in mortality gradient and excess deaths. For females in 1993-1998, a negative gradient of mortality by SEP was found, and cancer contributed the higher all-cause mortality in the higher SEP quintile. CONCLUSIONS: The relative importance of socioeconomic inequality in regional mortality of stroke decreased, while that of injury and suicide increased. The prevention of injury and suicide, in addition to stroke, in socioeconomically disadvantaged regions, and cancer in urban areas with higher SEP should be given priority.     

Primary care, income inequality, and self-rated health in the United States: a mixed-level analysis.

Using the 1996 Community Tracking Study household survey, the authors examined whether income inequality and primary care, measured at the state level, predict individual morbidity as measured by self-rated health status, while adjusting for potentially confounding individual variables. Their results indicate that distributions of income and primary care within states are significantly associated with individuals' self-rated health; that there is a gradient effect of income inequality on self-rated health; and that individuals living in states with a higher ratio of primary care physician to population are more likely to report good health than those living in states with a lower such ratio. From a policy perspective, improvement in individuals' health is likely to require a multi-pronged approach that addresses individual socioeconomic determinants of health, social and economic policies that affect income distribution, and a strengthening of the primary care aspects of health services.     

The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970-1998

OBJECTIVE: To assess the contribution of primary care systems to a variety of health outcomes in 18 wealthy Organization for Economic Cooperation and Development (OECD) countries over three decades. DATA SOURCES/STUDY SETTING: Data were primarily derived from OECD Health Data 2001 and from published literature. The unit of analysis is each of 18 wealthy OECD countries from 1970 to 1998 (total n = 504). STUDY DESIGN: Pooled, cross-sectional, time-series analysis of secondary data using fixed effects regression. DATA COLLECTION/EXTRACTION METHODS: Secondary analysis of public-use datasets. Primary care system characteristics were assessed using a common set of indicators derived from secondary datasets, published literature, technical documents, and consultation with in-country experts. PRINCIPAL FINDINGS: The strength of a country's primary care system was negatively associated with (a) all-cause mortality, (b) all-cause premature mortality, and (c) cause-specific premature mortality from asthma and bronchitis, emphysema and pneumonia, cardiovascular disease, and heart disease (p<0.05 in fixed effects, multivariate regression analyses). This relationship was significant, albeit reduced in magnitude, even while controlling for macro-level (GDP per capita, total physicians per one thousand population, percent of elderly) and micro-level (average number of ambulatory care visits, per capita income, alcohol and tobacco consumption) determinants of population health. CONCLUSIONS: (1) Strong primary care system and practice characteristics such as geographic regulation, longitudinality, coordination, and community orientation were associated with improved population health. (2) Despite health reform efforts, few OECD countries have improved essential features of their primary care systems as assessed by the scale used here. (3) The proposed scale can also be used to monitor health reform efforts intended to improve primary care.