Sam Harper

Global Variability in Fruit and Vegetable Consumption

BACKGROUND Low fruit and vegetable consumption is an important risk factor for chronic diseases, but for many (mainly developing) countries, no prevalence data have ever been published. This study presents data on the prevalence of low fruit and vegetable intake for 52 countries and for various sociodemographic groups and settings across these countries. METHODS Data from 196,373 adult participants from 52 countries taking part in the World Health Survey (2002-2003) were analyzed in the summer of 2008. Low fruit and vegetable consumption was defined according to the WHO guidelines of a minimum of five servings of fruits and/or vegetables daily. RESULTS Low fruit and vegetable consumption prevalence ranged from 36.6% (Ghana) to 99.2% (Pakistan) for men and from 38.0% (Ghana) to 99.3% (Pakistan) for women. Significant differences in the likelihood of low fruit and vegetable intake between men and women were found in 15 countries. The prevalence of low fruit and vegetable consumption tended to increase with age and decrease with income. Although urbanicity was not associated overall with low fruit and vegetable consumption, urban and rural differences were significant for 11 countries. CONCLUSIONS Overall, 77.6% of men and 78.4% of women from the 52 mainly low- and middle-income countries consumed less than the minimum recommended five daily servings of fruits and vegetables. Baseline global information on low fruit and vegetable consumption obtained in this study can help policymakers worldwide establish interventions for addressing the global chronic disease epidemic.

Explaining the social gradient in coronary heart disease: comparing relative and absolute risk approaches

Study objectives: There are contradictory perspectives on the importance of conventional coronary heart disease (CHD) risk factors in explaining population levels and social gradients in CHD. This study examined the contribution of conventional CHD risk factors (smoking, hypertension, dyslipidaemia, and diabetes) to explaining population levels and to absolute and relative social inequalities in CHD. This was investigated in an entire population and by creating a low risk sub-population with no smoking, dyslipidaemia, diabetes, and hypertension to simulate what would happen to relative and social inequalities in CHD if conventional risk factors were removed. Design, setting, and participants: Population based study of 2682 eastern Finnish men aged 42, 48, 54, 60 at baseline with 10.5 years average follow up of fatal (ICD9 codes 410–414) and non-fatal (MONICA criteria) CHD events. Main results: In the whole population, 94.6% of events occurred among men exposed to at least one conventional risk factor, with a PAR of 68%. Adjustment for conventional risk factors reduced relative social inequality by 24%. However, in a low risk population free from conventional risk factors, absolute social inequality reduced by 72%. Conclusions: Conventional risk factors explain the majority of absolute social inequality in CHD because conventional risk factors explain the vast majority of CHD cases in the population. However, the role of conventional risk factors in explaining relative social inequality was modest. This apparent paradox may arise in populations where inequalities in conventional risk factors between social groups are low, relative to the high levels of conventional risk factors within every social group. If the concern is to reduce the overall population health burden of CHD and the disproportionate population health burden associated with the social inequalities in CHD, then reducing conventional risk factors will do the job.

An Overview of Methods for Monitoring Social Disparities in Cancer with an Example Using Trends in Lung Cancer Incidence by Area-Socioeconomic Position and Race-Ethnicity, 1992–2004

The authors provide an overview of methods for summarizing social disparities in health using the example of lung cancer. They apply four measures of relative disparity and three measures of absolute disparity to trends in US lung cancer incidence by area-socioeconomic position and race-ethnicity from 1992 to 2004. Among females, measures of absolute and relative disparity suggested that area-socioeconomic and race-ethnic disparities increased over these 12 years but differed widely with respect to the magnitude of the change. Among males, the authors found substantial disagreement among summary measures of relative disparity with respect to the magnitude and the direction of change in disparities. Among area-socioeconomic groups, the index of disparity increased by 47% and the relative concentration index decreased by 116%, while for race-ethnicity the index of disparity increased by 36% and the Theil index increased by 13%. The choice of a summary measure of disparity may affect the interpretation of changes in health disparities. Important issues to consider are the reference point from which differences are measured, whether to measure disparity on the absolute or relative scale, and whether to weight disparity measures by population size. A suite of indicators is needed to provide a clear picture of health disparity change.

Trends in Area-Socioeconomic and Race-Ethnic Disparities in Breast Cancer Incidence, Stage at Diagnosis, Screening, Mortality, and Survival among Women Ages 50 Years and Over (1987-2005)

Background: Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer death among women in the United States and varies systematically by race-ethnicity and socioeconomic status. Previous research has often focused on disparities between particular groups, but few studies have summarized disparities across multiple subgroups defined by race-ethnic and socioeconomic position. Methods: Data on breast cancer incidence, stage, mortality, and 5-year cause-specific probability of death (100 − survival) were obtained from the Surveillance, Epidemiology, and End Results program and data on mammography screening from the National Health Interview Survey from 1987 to 2005. We used four area-socioeconomic groups based on the percentage of poverty in the county of residence (<10, 10-15, 15-20, +20%) and five race-ethnic groups (White, Black, Asian, American Indian, and Hispanic). We used summary measures of disparity based on both rate differences and rate ratios. Results: From 1987 to 2004, area-socioeconomic disparities declined by 20% to 30% for incidence, stage at diagnosis, and 5-year cause-specific probability of death, and by roughly 100% for mortality, whether measured on the absolute or relative scale. In contrast, relative area-socioeconomic disparities in mammography use increased by 161%. Absolute race-ethnic disparities declined across all outcomes, with the largest reduction for mammography (56% decline). Relative race-ethnic disparities for mortality and 5-year cause-specific probability of death increased by 24% and 17%, respectively. Conclusions: Our analysis suggests progress towards race-ethnic and area-socioeconomic disparity goals for breast cancer, especially when measured on the absolute scale. However, greater progress is needed to address increasing relative socioeconomic disparities in mammography and race-ethnic disparities in mortality and 5-year cause-specific probability of death. (Cancer Epidemiol Biomarkers Prev 2009;18(1):121–31)

Implicit value judgments in the measurement of health inequalities.

CONTEXT Quantitative estimates of the magnitude, direction, and rate of change of health inequalities play a crucial role in creating and assessing policies aimed at eliminating the disproportionate burden of disease in disadvantaged populations. It is generally assumed that the measurement of health inequalities is a value-neutral process, providing objective data that are then interpreted using normative judgments about whether a particular distribution of health is just, fair, or socially acceptable. METHODS We discuss five examples in which normative judgments play a role in the measurement process itself, through either the selection of one measurement strategy to the exclusion of others or the selection of the type, significance, or weight assigned to the variables being measured. FINDINGS Overall, we find that many commonly used measures of inequality are value laden and that the normative judgments implicit in these measures have important consequences for interpreting and responding to health inequalities. CONCLUSIONS Because values implicit in the generation of health inequality measures may lead to radically different interpretations of the same underlying data, we urge researchers to explicitly consider and transparently discuss the normative judgments underlying their measures. We also urge policymakers and other consumers of health inequalities data to pay close attention to the measures on which they base their assessments of current and future health policies.

Do Medical Marijuana Laws Increase Marijuana Use? Replication Study and Extension

PURPOSE To replicate a prior study that found greater adolescent marijuana use in states that have passed medical marijuana laws (MMLs), and extend this analysis by accounting for confounding by unmeasured state characteristics and measurement error. METHODS We obtained state-level estimates of marijuana use from the 2002 through 2009 National Survey on Drug Use and Health. We used 2-sample t-tests and random-effects regression to replicate previous results. We used difference-in-differences regression models to estimate the causal effect of MMLs on marijuana use, and simulations to account for measurement error. RESULTS We replicated previously published results showing higher marijuana use in states with MMLs. Difference-in-differences estimates suggested that passing MMLs decreased past-month use among adolescents by 0.53 percentage points (95% confidence interval [CI], 0.03-1.02) and had no discernible effect on the perceived riskiness of monthly use. Models incorporating measurement error in the state estimates of marijuana use yielded little evidence that passing MMLs affects marijuana use. CONCLUSIONS Accounting for confounding by unmeasured state characteristics and measurement error had an important effect on estimates of the impact of MMLs on marijuana use. We find limited evidence of causal effects of MMLs on measures of reported marijuana use.

Determinants of Increased Opioid-Related Mortality in the United States and Canada, 1990–2013: A Systematic Review

We review evidence of determinants contributing to increased opioid-related mortality in the United States and Canada between 1990 and 2013. We identified 17 determinants of opioid-related mortality and mortality increases that we classified into 3 categories: prescriber behavior, user behavior and characteristics, and environmental and systemic determinants. These determinants operate independently but interact in complex ways that vary according to geography and population, making generalization from single studies inadvisable. Researchers in this area face significant methodological difficulties; most of the studies in our review were ecological or observational and lacked control groups or adjustment for confounding factors; thus, causal inferences are difficult. Preventing additional opioid-related mortality will likely require interventions that address multiple determinants and are tailored to specific locations and populations.

Use of relative and absolute effect measures in reporting health inequalities: structured review

Objective To examine the frequency of reporting of absolute and relative effect measures in health inequalities research. Design Structured review of selected general medical and public health journals. Data sources 344 articles published during 2009 in American Journal of Epidemiology, American Journal of Public Health, BMJ, Epidemiology, International Journal of Epidemiology, JAMA, Journal of Epidemiology and Community Health, The Lancet, The New England Journal of Medicine, and Social Science and Medicine. Main outcome measures Frequency and proportion of studies reporting absolute effect measures, relative effect measures, or both in abstract and full text; availability of absolute risks in studies reporting only relative effect measures. Results 40% (138/344) of articles reported a measure of effect in the abstract; among these, 88% (122/138) reported only a relative measure, 9% (13/138) reported only an absolute measure, and 2% (3/138) reported both. 75% (258/344) of all articles reported only relative measures in the full text; among these, 46% (119/258) contained no information on absolute baseline risks that would facilitate calculation of absolute effect measures. 18% (61/344) of all articles reported only absolute measures in the full text, and 7% (25/344) reported both absolute and relative measures. These results were consistent across journals, exposures, and outcomes. Conclusions Health inequalities are most commonly reported using only relative measures of effect, which may influence readers’ judgments of the magnitude, direction, significance, and implications of reported health inequalities.

Social Determinants and the Decline of Cardiovascular Diseases: Understanding the Links

This article reviews the historical declines in cardiovascular mortality and provides an overview of the contribution of social and economic factors to disease change. We document the magnitude of declines in cardiovascular diseases and the major role of changes in conventional risk factors, and we review the contributions of social determinants to changes in disease rates. We conclude by arguing that understanding patterns and trends of social inequalities in cardiovascular disease and its risk factors requires consideration of the specific intersections of health and social exposures acting across the life course in different settings, in both time and place.

The contribution of material, psychosocial, and behavioral factors in explaining educational and occupational mortality inequalities in a nationally representative sample of South Koreans: Relative and absolute perspectives

The contributions of material, psychosocial, and behavioral factors in explaining socioeconomic inequalities in health have been explored in many Western studies. Most prior investigations have looked at relative abilities to explain such inequalities. In addition, little research focuses on Asian countries, despite the fact that the prevalence and socioeconomic distribution of risk factors for mortality are different there. This study examined relative and absolute abilities of material, psychosocial, and behavioral pathways to explain educational and occupational inequalities in mortality in a nationally representative sample from South Korea. The 1998 and 2001 National Health and Nutrition Examination Survey data were pooled and linked to national mortality data. Of 8366 men and women over 30 years of age, 310 died between 1999 and 2005. Nine pathway variables were examined: three material factors (income, health insurance, and car ownership status), three psychosocial factors (depression, stress, and marital status), and three behavioral factors (smoking, alcohol consumption, and physical exercise). The relative risk and relative index of inequality were used as measures of relative inequality, and risk differences and the slope index of inequality were used as measures of absolute inequality. Material factors explained a total of 29.0% of the excess in relative risk for education and 50.0% of the excess in relative risk for occupational class. Material factors explained 78.6% of the excess in absolute mortality difference for education and 41.1% for occupational class. Psychosocial factors for both education and occupational class had a relative and absolute explanatory power of less than 15%. Behavioral factors showed a relative explanatory power of about 15%, but absolute explanatory power reached 84.0% for education and 105.4% for occupational class. However, the number of deaths used to calculate the absolute explanatory power was small. Results of this study suggest that absolute socioeconomic mortality inequalities could be substantially reduced if behavioral risk factors were reduced in the whole population.