HCPDS Working Paper Series

Our descriptive study examined current associations (2022-2024) between four US state-level political metrics (political ideology based on voting records of US House and Senate members; US state political party control; state policies enacted; and voter political lean) and eight health state-level outcomes spanning the lifecourse: infant mortality; premature mortality; health insurance (adults aged 35-64); vaccination for children and persons aged ≥65 (flu; COVID-19 booster); maternity care deserts; and food insecurity; for the first three outcomes, we also examined trends in associations (2012-2024). For all political metrics, higher state-level political conservatism was associated with worse health outcomes. For example, comparing states with Republican vs. Democratic trifectas, current premature mortality rates (2022-2024) were worse (-25.5 deaths per 100,000 person-years, 95% confidence interval [CI] -46.2, -4.4) as was percent uninsured (-2.8, 95% CI -4.9, -0.6), with conservative states’ worse health outcomes evident in every presidential election year. Additionally, the sharp rise of premature mortality rates in 2018-2021 started at higher levels and was greater in more conservative vs. more liberal states. These results can inform health professionals, policymakers, elected officials, civil society groups, and the broader electorate, especially in an election year.

The findings published in this working paper are featured in The Nation.

The findings published in this working paper are featured in The Guardian.

The working paper is now published in Health Affairs Scholar

Inferring the severity of an emerging infectious agent presents specific challenges due to the inevitably imperfect state of data early in an epidemic. Here we specifically consider the additional impact of existing population immunity on estimates of intrinsic virulence, using the example of early evidence of the Omicron variant of SARS-CoV-2 emerging in South Africa. Without accounting for vaccination rates and prior infections, among other factors, the true risk of severe infection will be systematically underestimated. At the time of writing it is premature to consider Omicron infections to be intrinsically milder that those caused by preceding variants.

We were honored to have our working paper series provide a platform for this time-sensitive article on the challenges around inferring the severity of the omicron variant that is now published in The New England Journal of Medicine.

Those who are not employed during their 50s – and who may not be candidates for working into their 60s – are frequently invisible in the working longer discussion. We bring these individuals back into the conversation by examining who is and is not working in their 50s, the stability of individuals’ employment in their 50s, and their likelihood of working into their 60s. We find that those who lack stable employment during their 50s are disproportionately non-white, women, and those without college degrees. While disadvantaged groups start from a lower base, employment rates fall by about 20 percentage points for all groups between ages 50 and 60. We also find that continuous employment during one’s 50s appears to be a critical foundation for working longer, but about half of Americans do not have continuous employment during their 50s. Policies that improve the quality and consistency of employment in late middle age may increase rates of working longer.

Latino immigrants face hiring disadvantages in the United States labor market compared to native-born Latinos, which may be due to human capital, legal status, or employer bias. However, it is difficult to adjudicate between these explanations because most scholarship documenting hiring inequalities focuses on workers’ experiences, not employers’ actions. This prevents understanding whether employer discrimination is a mechanism of nativity status inequalities in hiring, particularly among the growing share of Latinos with college degrees. I conduct a correspondence audit study of 1,364 jobs in eight metros to test whether employers screen out college-educated Latino men based on nativity and legal status. Employers were twice as likely to call back native-born as immigrant Latinos. Paradoxically, however, employers called back documented, work-authorized Latinos at almost the same low rates as undocumented Latinos without the right to work. A national survey experiment of 468 Human Resources representatives, and interviews with 23 HR representatives and immigration lawyers, reveal that individual concerns about immigrants’ English language ability, and organizational concerns about immigrants’ deportability, explain why employers are reluctant to hire any Latino immigrant. The results highlight the power of both nativist attitudes and immigration laws for hampering the employment chances of even documented, college-educated Latinos.

Social Forces (June 18, 2022)

This Op-Ed published in the Chicago Tribune on February 7, 2022, was based on this working paper.

In the United States, the integration experiences of immigrants depend in part on whether they are recognized as refugees or as economic migrants. Unlike economic migrants, refugees receive federal resources to help find employment, and this distinction raises important questions about the role such government support plays in migrants’ labor market integration. First, drawing on nationally representative data from the New Immigrant Survey, we find that despite their early access to government-funded employment services, refugees actually experience employment declines the longer they live in the United States. Next, drawing on interviews with sixty-one refugee-serving organizations across the country, we highlight three structural weaknesses in the federal refugee resettlement process that help account for these employment declines: (1) retrenched resettlement funding, (2) a logic of self-sufficiency prioritizing rapid employment in generally undesirable jobs, and (3) siloed networks of refugee-serving organizations. Our findings have important implications for immigrant integration, the welfare state, and how nonprofit organizations shape inequality.

Social Problems (published online on January 5, 2022).

COVID-19 monitoring dashboards and data journalism have actively been documenting how, among US regions, the US South has experienced the brunt of the surge associated with the delta variant, which took off in July 2021, at a time when all US adults had been eligible for vaccination for at least 3 months. However, less attention has been given to regional heterogeneity in COVID-19 inequities. In this brief report, we document that during the period July 1 – September 15, 2021, the US South not only has experienced the highest COVID-19 case and death rates (per 100,000 person-years), as previously noted, but also that this region has the highest COVID-19 inequities, as measured using a variety of county-level social metrics. For example, comparing rates among people living in the highest vs. lowest poverty counties, the rate ratios and 95% confidence intervals for COVID-19 incidence rates, by region, were as follows: South: 2.07 (95% CI 1.53, 2.18); Northeast: 1.33 (95% CI 0.90, 1.97); Midwest: 1.12 (95% CI 0.87, 1.45); West: 1.35 (95% CI 0.83, 2.25); for COVID-19 mortality rates, they were: South: 5.83 (95% CI 2.33, 14.49); Northeast: 3.66 (95% CI 0.93, 14.43); Midwest: 2.62 (95% CI 1.36, 5.04); West: 3.25 (95% CI 0.67, 15.87). Additionally, considered across the diverse social metrics employed, the highest COVID-19 burden occurred in the US South in counties with the greatest Republican lean in the 2020 election (case incidence rate per 100,000 person-years: 23,541; 95% CI 22,868, 24,234; death rate per 100,000 person-years: 197; 95% CI 186, 208), and the lowest in the US Northeast in counties with the lowest poverty rate (case incidence rate per 100,000 person years: 5,420; 95% CI 3,755, 7,822; death rate: 12, 95% CI 3,46). While attention to overall US inequities in COVID-19 rates is important, so too is regional specificity, and the variations in rates and inequities across regions provides valuable information regarding disease burdens that in principle could be prevented.

Descriptions and monitoring of the social and spatial population distribution of COVID-19 cases and deaths in the US have largely relied on individual- and county-level sociodemographic data and vulnerability indices that draw primarily or exclusively from data available in US health records and US census data. In this brief report, using US data from September 1, 2020 to September 15, 2021, we provide empirical evidence demonstrating that county-level data on political lean (Republican vs. Democrat for the 2020 US presidential election) adds critical information to understanding population distributions of COVID cases and deaths – and also document the importance of socioeconomic variables in addition to data on racialized groups. In particular, during the period from July 1, 2021-September 15 (corresponding to the Delta surge, occurring when COVID-19 vaccines were authorized for all US adults for at least 3 months or more), the two county-level variables that most sharply differentiated risk comparing the highest to lowest quintiles for COVID-19 rates (per 100,000 person-years) were: (a) political lean: highest Republican lean vs. highest Democratic lean, for cases: rate ratio (RR)=2.39 (95% confidence interval [CI] 2.25, 2.55) and for deaths: RR=3.34 (95% CI 2.99, 3.73), and (b) percent below poverty line, for cases: RR 1.93 (95% CI 1.15, 2.4) and for deaths: RR=5.08 (95% CI 3.14, 8.97). By contrast, the least differentiation was provided by % people of color (highest vs. lowest quintile): for cases, RR=0.95 (95% CI 0.89, 1.02), and for deaths: 0.83 (95% CI 0.74, 0.93). However, combining these single variables with political lean magnified the risk contrast between county quintiles. Thus, people residing in the counties jointly with the highest poverty and highest political lean toward Republicans were nearly 6 times more likely to die (rate ratio: 5.90; 95% CI 4.95, 7.07) from COVID-19 compared to those residing in the counties jointly with the lowest poverty and highest political lean toward Democrats. Additionally, people residing in counties jointly with the highest % people of color and highest political lean toward Republicans were almost 5 times more likely to die (rate ratio: 4.77, 95% CI 3.70, 6.20) from COVID-19 compared to people residing in counties jointly with the lowest % people of color and highest political lean toward Democrats. We accordingly posit that county-level political lean is a crucial variable that should be used routinely to monitor county-level trends in COVID-19 cases and mortality, alongside and in conjunction with sociodemographic and socioeconomic data.

Visually depicting and contrasting the number and proportion of persons who become hospitalized with and die from COVID-19 among the fully vaccinated versus the unvaccinated populations offers a powerful argument for why getting vaccinated matters – to protect against preventable suffering due to COVID-19 among people’s loved ones, themselves personally, and their communities. Communicating this information clearly is an urgent task. In this brief report, we draw on publicly reported data available for 12 states (for January through July 2021) to illustrate the profoundly elevated risk of needless suffering and death among those who are not vaccinated vs. are fully vaccinated. We focus on the relative risk of hospitalization and death for the unvaccinated compared to the vaccinated to underscore the consequences of continued vaccine resistance and inequities in access. Varying by state, the unvaccinated are 5 to 133 times more likely to be hospitalized and 9 to 141 times more likely to die. This state variation likely reflects differences in age (among the total population as well as those vaccinated and not vaccinated), community health profiles, public health policies and investment, inequities in exposure to the virus that causes COVID-19, i.e., SARS-CoV-2 (e.g., among essential workers), and reasons for not being vaccinated (including lack of access, medical or religious exceptions, or ideological opposition). Considered together, these risks are on par with or vastly exceed the risk of lung cancer due to smoking or risk of injury or death in a car crash if not wearing a seat belt. We also provide a visual argument as to why focusing on the percentage of hospitalized or deceased persons diagnosed with COVID-19 who are vs. are not vaccinated is misleading, noting that once 100% of the population is vaccinated, all persons who contract or die from COVID-19 will have been vaccinated, but this number of persons will be tiny compared to the number who would have become ill or died had they not been vaccinated. Despite concerns about reduced vaccine efficacy associated with the rise of newer SARS-CoV-2 variants, data from these 12 states are consistent with continued vaccine efficacy. We will follow-up this brief visual paper with a more detailed and rich scientific manuscript that provides the mathematical, conceptual, and empirical foundations of our visual argument.

Background: Although educational attainment is a routinely reported data element on US death certificates, data on COVID-19 deaths were not reported by educational level, let alone stratified by race/ethnicity and education, in government health statistics during the first year of the pandemic under the Trump administration. On February 2, 2021, the US National Center for Health Statistics published a national-level data table of COVID-19 deaths stratified by race/ethnicity and education, newly enabling intersectional analysis of inequities in relation to racialized and educational groups. Methods: We analyzed all COVID-19 deaths recorded for January 1, 2020 through January 31, 2021 (N=413,196) in relation to individual-level death certificate data on race/ethnicity and educational level, and corresponding US population data. We calculated rates per 100,000 person-years and associated 95% confidence limits, and estimated incidence rate ratios (IRR) using saturated Poisson loglinear models. Following STROBE guidelines for the presentation of interactions, we computed IRRs for (a) racial/ethnic inequities within educational groups; (b) educational inequities within racial/ethnic groups; and (c) intersectional inequities relative to a common reference group (Non-Hispanic Whites with a postgraduate degree). Results: First, regarding racialized inequities in COVID-19 mortality, crude rates were significantly greater among Non-Hispanic Blacks (IRR 1.3, 95% CI 1.3, 1.3), Hispanics (IRR 1.1, 95% CI 1.1, 1.1), and Non-Hispanic American Indian or Alaskan Natives (IRR 1.7, 95% CI 1.7, 1.7) and lower among Non-Hispanic Asian Pacific Islanders (IRR 0.6, 95% CI 0.6, 0.6) compared with Non-Hispanic Whites. Second, substantially elevated rates occurred for persons with less than a high school education (IRR 5.3, 95% CI 5.3, 5.3), high school graduates (IRR 3.4, 95% CI 3.4, 3.4), and some college (IRR 1.3, 95% CI 1.3, 1.3) relative to those with a postgraduate degree; rates among college graduates were virtually identical to those with a postgraduate degree. Analysis of joint inequities by race/ethnicity and education relative to a common reference group (Non-Hispanic Whites with a postgraduate degree, the theoretically most advantaged group) showed that inequities in mortality are dominated by the steep educational gradient in all groups, with those in the less than high school group having rate ratios ranging from 3.3 (Non-Hispanic Asian Pacific Islanders) to 7.8 (Non-Hispanic American Indian and Alaskan Natives) relative to the reference group and those in the high school graduate group having rate ratios ranging from 2.1 (Hispanics and Non-Hispanic Asian Pacific Islanders) to 3.5 (Non-Hispanic Whites and Non-Hispanic American Indian or Alaskan Natives). We found strong statistical evidence of interaction between race/ethnicity and educational attainment on both the additive and multiplicative scales. Conclusions: The release of these long overdue data on COVID-19 mortality rates by race/ethnicity and educational attainment provide valuable insight into who has borne the unequal burden of COVID-19 death in the United States. Timely reporting of COVID-19 outcomes by race/ethnicity, socioeconomic measures including education and occupation, age, and gender must be a priority to ensure transparency and accountability and to support action to reduce the continuing impact of the pandemic on those most adversely impacted by structural injustice.

This paper presents novel data on the comingled miseries of COVID-19, food insecurity, and housing insecurity. It employs the real-time economic data from the US Household Pulse Survey (in contrast to most analyses that rely on economic data from prior years, which cannot capture the economic shock of the pandemic), in conjunction with novel data on how these types of economic insecurity jointly vary by racialized group, educational level, and place. The information presented supports why the US government should “go big” in order to, in the words of the US constitution, “promote the general welfare,” so as to pull this country together.

The New York Daily News: Attack America’s overlapping miseries: Why going big on relief is an economic, public health and moral imperative

The new Feb 2 MMWR report – which documented that fully 48.1% of persons vaccinated against COVID-19 in the 1st month of rollout (December 14, 2020-January 14, 2021) were missing data on race/ethnicity (whereas only 0.1% and 3% were missing data respectively on age and sex) – was tellingly published on “Groundhog Day,” and evokes the phrase’s other contemporary meaning of an endlessly repeating time-loop (per the 1993 comic film of that title). We also update the data on COVID-19 cases missing data on race/ethnicity: for the most recent period (Dec 2, 2020-Feb 3, 2021), it stands at 33%, only a modest decline since the 43% missing we reported in the HCPDS Working Paper for Aug 28-Sept 16, 2020.

The Lancet: Missing again: US racial and ethnic data for COVID-19 vaccination

Discussions in the United States about criteria for ensuring equitable vaccine distribution for COVID-19 have focused on both individual and community characteristics. Is it reasonable, however, to assume that US community characteristics have a clear-cut relationship to risk of COVID-19 in the context of a dynamic and increasingly out-of-control pandemic? To test this hypothesis, we examined temporal and regional variation in the correlations of a range of county-level social and economic metrics, including the CDC’s social vulnerability index, with COVID-19 case and death rates per capita, spanning from February 1, 2020 through November 10, 2020: for the US as a whole, and for four regions – Northeast, Midwest, South, and West. Consistent with our hypothesis, the observed correlations for each metric varied considerably by time and by region, as did the relative strength of the correlations for the economic and racial/ethnic variables – and as of early November 2020, all correlations were under 0.3 and most hovered close to 0. Our findings offer an important warning against using static US county-level community characteristics to guide equitable allocation of COVID-19 vaccines.

In India, Parliamentary Constituencies (PCs) could serve as a regional unit of COVID-19 monitoring that facilitates evidence-based policy decisions. In this study, we presented the first estimates of COVID-19 cumulative cases and deaths per 100,000 population, and the case fatality rate (CFR) between January 7th, 2020 and October 18th, 2020 across 543 PCs and 721 districts of India. We adopted a novel geographic information, science-based methodology called crosswalk to estimate COVID-19 outcomes at the PC-level from district-level information. We found a substantial variation of COVID-19 burden within each state and across the country. Access to PC-level and district-level COVID-19 information can enhance both central and regional governmental accountability of safe reopening policies.

COVID-19 doesn’t care who you are or what you believe. It does not respect political ideology or partisan rancor. As far as the virus SARS-COV-2 is concerned, all that matters is opportunities for exposure and transmission: are you available as a potential host – or not. For people, what matters are the actions you are able – or not able or not permitted – to take to protect yourself, your family, and your community, from exposure to the virus. True, COVID-19 is a global pandemic – but it is simultaneously as local and as intimate as the contacts you have where you live, work, travel, and the public spaces you visit. The maps of the changing political geography of COVID-19 make this vividly clear. From mid-March to June, the excess death rates were highest in states leaning Democratic, and the more strongly they tilted in that direction, the greater the excess. However, in mid-July, the pattern reversed, with the burden of excess death rates growing highest in Republican leaning states. As we enter the fall, the rates of excess deaths are now highest in the states that lean most Republican. Reducing risk of exposure is key.

The United States (US) has been among those nations most severely affected by the first—and subsequent—phases of the pandemic of COVID-19 disease caused by SARS-CoV-2. With only 4% of the worldwide population, the US has seen about 22% of COVID-19 deaths. Despite formidable advantages in resources and expertise, presently the per capita mortality rate is over 585/million, respectively 2.4 and 5 times higher compared to Canada and Germany. As we enter Fall 2020, the US is enduring ongoing outbreaks across large regions of the country. Moreover, within the US, an early and persistent feature of the pandemic has been the disproportionate impact on populations already made vulnerable by racism and dangerous jobs, inadequate wages, and unaffordable housing, and this is true for both the headline public health threat and the additional disastrous economic impacts. In this article we assess the impact of missteps by the Federal Government in three specific areas: the introduction of the virus to the US and the establishment of community transmission; the lack of national COVID-19 workplace standards and lack of personal protective equipment (PPE) for workplaces as represented by complaints to the Occupational Safety and Health Administration (OSHA) which we find are correlated with deaths 17 days later (=0.845); and the total excess deaths in 2020 to date, which already total more than 230,000 and exhibit severe inequities in race/ethnicity including among younger age groups.

European Journal of Epidemiology:“COVID-19: US federal accountability for entry, spread, and inequities—lessons for the future.”

We report novel data on persistence of missing racial/ethnic data for COVID-19 cases in the United States, despite a federal policy that went into effect on June 4, 2020, which stated reporting of such data would be mandatory, effective by no later than August 1, 2020. To our knowledge, no report has documented whether or not US federal agencies or states are in compliance with this regulation. Our key finding, based on publicly available data at the CDC website, is that racial/ethnic data was missing for fully 43% of the 422,057 COVID-19 cases recorded between August 28, 2020 and September 16, 2020. Publicly available data at the COVID-19 Racial Data Tracker likewise indicates that as of September 13, 2020, 37.5% of the recorded 6,448,573 cases were missing data on race, and among states, the percent missing ranged from 0% to 100%, with a median value of 21%. These findings suggest that compliance with regulations to report data on race/ethnicity for US COVID-19 cases is inadequate and continues to hamper understanding of and efforts to mitigate racial/ethnic inequities in COVID-19.

The Lancet (correspondence): “US racial and ethnic data for COVID-19 cases: still missing in action”

Data visualizations of the COVID-19 pandemic in the United States often have presented case and death rates by state in separate visualizations making it difficult to discern the temporal relationship between these two epidemiological metrics. By combining the COVID-19 case and death rates into a single visualization we have provided an intuitive format for depicting the relationship between cases and deaths. Moreover, by using animation we have made the temporal lag between cases and subsequent deaths more obvious and apparent. This work helps to inform expectations for the trajectory of death rates in the United States given the recent surge in case rates.

Importance: Excess COVID-19 mortality has been described among Non-Hispanic Blacks (NHB), Hispanics and Non-Hispanic American Indians/Alaska Natives (NHAIAN), compared to non-Hispanic Whites (NHW), but not in relation to age at death. Recent release of national COVID-19 deaths by racial/ethnic group now permit analysis of age-specific mortality rates. Objective: To examine variation in age-specific mortality rates by racial/ethnicity and calculate its impact using Years of Potential Life Lost (YPLL). Design: This is a descriptive study using the most recently publicly available data on COVID-19 deaths, with population data drawn from the US Census Setting: United States Participants: All persons for whom there were reported deaths, COVID-19 deaths and reported racial/ethnicity February 1, 2020-May 20, 2020 Results: Age-standardized rate ratios relative to NHW were 3.6 (95% CI 3.5, 3.7) for NHB, 2.6 95% CI 2.4, 2.7) for Hispanics, 1.2 (0.8, 1.6) for NHAIAN, and 1.7 (1.6, 1.9) for NHAPI. By contrast, NHB rate ratios relative to NHW were as high as 7.3 (95% CI 5.6, 9.5) for 25-34 year old, 9.0 (95% CI 7.6, 10.8) for 35-44 year old, and 6.9 (95% CI 6.3, 7.6) for 45-54 year old. Even at older ages, NHB rate ratios were between 1.9 and 5.7. Similarly, rate ratios for Hispanics vs. NHW were 5.5 (95% CI 4.2, 7.2), 7.9 (95% CI 6.7, 9.3), and 5.8 (95% CI 5.3, 6.3) for corresponding age strata, with remaining rate ratios ranging from 1.4 to 4.1. Rate ratios for NHAIAN were similarly high, ranging from 1.4 to 8.2 over ages 25-75, and only dipping below 1.0 for age 75-84 and 85+. Among NHAPI, rate ratios ranged from 2.2 to 2.4 for ages 25-75 and were 1.6 and 1.2 for age 75-84 and 85+ respectively. As a consequence, more years of potential life lost were experienced by African Americans and Latinos than whites, although the white population is 3-4 fold larger. Conclusion/Relevance: This analysis makes clear the importance of examining age-specific mortality rates and underscore how age standardization can obscure extreme variations within age strata. Data that permit age-specific analyses should be routinely publicly available.

PLOS Medicine: “Variation in racial/ethnic disparities in COVID-19 mortality by age in the United States: A cross-sectional study.”

Despite the paucity of adequate data on race/ethnicity – and no data on socioeconomic position – in US national data on COVID-19 mortality, both investigative journalism and some state and local health departments are beginning to document evidence of the greater mortality burden of COVID-19 on communities of color and low-income communities. To date, such documentation has been in relation to deaths categorized as due to COVID-19. However, in a context when assignment of cause of death to COVID-19 is dynamic and incomplete, given developing scientific evidence, one important strategy for assessing differential impacts of COVID-19 is that of evaluating the overall excess of deaths, as compared to the same time period in prior years. We employ this approach in this working paper and provide a transparent, easy-to-replicate methodology that relies on the reported data (i.e., no model-based estimates or complex modeling assumptions) and that can be readily used by any local or state health agency to monitor the social patterning of excess mortality rates during the COVID-19 pandemic. Key findings are that the surge in excess death rates, both relative and absolute, was evident starting in early April, and was greater in city/towns and ZCTAs with higher poverty, higher household crowding, higher percentage of populations of color, and higher racialized economic segregation. These data provide the backbone to a story that is being published in the Boston Globe, with this Working Paper released following publication of this story (on May 9, 2020), available at: https://www.bostonglobe.com/2020/05/09/nation/disparities-push-coronavirus-death-rates-higher/

The Boston Globe: A new analysis: Coronavirus death rate surged in Massachusetts locations that already faced challenges

American Journal of Public Health: “COVID-19 and Overall Mortality Inequities in the Surge in Death Rates by Zip Code Characteristics: Massachusetts, January 1 to May 19, 2020”

No national, state, or local public health monitoring data in the US currently exist regarding the unequal economic and social burden of COVID-19. To address this gap, we draw on methods of the Public Health Disparities Geocoding Project, whereby we merge county-level cumulative death counts with population counts and area-based socioeconomic measures (ABSMs: % below poverty, % crowding, and % population of color, and the Index of Concentration at the Extremes) and compute rates, rate differences, and rate ratios by category of county-level ABSMs. To illustrate the performance of the method at finer levels of geographic aggregation, we analyze data on (a) confirmed cases in Illinois zip codes and (b) positive test results in New York City ZIP codes with ZIP code level ABSMs. We detect stark gradients though complex gradients in COVID-19 deaths by county-level ABSMs, with dramatically increased risk of death observed among residents of the most disadvantaged counties. Monotonic socioeconomic gradients in Illinois confirmed cases and New York City positive tests by ZIP code level ABSMs were also observed. We recommend that public health departments use these straightforward cost-effective methods to report on social inequities in COVID-19 outcomes to provide an evidence base for policy and resource allocation.

Journal of Public Health Management & Practice: “Revealing the Unequal Burden of COVID-19 by Income, Race/Ethnicity, and Household Crowding: US County Versus Zip Code Analyses.”

In India, data on key developmental indicators that formulate policies and interventions are routinely available for the administrative units of districts but not for the political units of Parliamentary Constituencies (PC). Members of Parliament (MPs) in the Lok Sabha, each representing 543 PCs as per the 2014 India map, are the representatives with the most direct interaction with their constituents. The MPs are responsible for articulating the vision and the implementation of public policies at the national level and for their respective constituencies. In order for MPs to efficiently and effectively serve their people, and also for the constituents to understand the performance of their MPs, it is critical to produce the most accurate and up-to-date evidence on the state of health and well-being at the PC-level. However, absence of PC identifiers in nationally representative surveys or the Census has eluded an assessment of how a PC is doing with regards to key indicators of nutrition, health and development. In this report, we present PC estimates for 100+ indicators of nutrition, health and development derived from two data sources.

Journal of Development Policy and Practice: “From Administrative to Political Evaluation: Estimating Water, Sanitation, and Hygiene Indicators for Parliamentary Constituencies in India”

RESEARH PROJECT – Burden of Disease and Deprivation in India across Micro and Macro Public Policy Units: A grant from the Bill and Melinda Gates Foundation is funding further research with the aim of improving precision public policy, public financing, and governance in India related to indicators of population health and development.

Nutritional well-being is central for achievement of several prominent national and international development goals. Despite considerable efforts and increasing policy commitments, India is yet to witness meaningful reductions in the burden of child undernutrition. We analyse the latest National Family Health Survey to develop critical policy insights to catalyse the reductions in child anthropometric failures in India. We describe that the POSHAN targets are far from modest and will require greater contribution from poor-performing states. The two fundamental concerns as reflected by this analysis are non-response of economic growth on nutritional well-being and greater burden among the poor. This calls for strengthening developmental finance for socioeconomic upliftment as well as enhanced programmatic support for nutritional interventions. The gaps in analytical inputs for programmatic purposes also deserves attention to unravel intricacies that otherwise remain obscured through customary enquiries. On one hand, this may serve well to improve policy targeting and on the other can help comprehend the nature and reasons of heterogeneities and inequities in nutritional outcomes across groups and geographies. In conclusion, we recommend strengthening analytical capacities of programme managers and health functionaries.

In this brief report, and building on a previous study (6), for the first time, we present robust estimates on five indicators of child malnutrition (i.e., stunting, underweight, wasting, low birth weight, anaemia) for each PC in India. We provide ranking of the PCs both on the (i) average prevalence of the five indicators; and (ii) the degree of “Between-Village” inequality in the prevalence estimate on the five indicators. Thus, even if a PC is doing well on average, large inequalities within a PC (between its villages) suggests the need for further precision geo-targeting.

SSM – Population Health: “Estimating the burden of child malnutrition across parliamentary constituencies in India: A methodological comparison.”

In India, excess female mortality, primarily concentrated in the postneonatal period, is well documented. Deaths in early childhood are also known to be patterned by socioeconomic factors. This study examines sex differentials and sex-specific wealth gradients in neonatal, postneonatal, and child mortality in India using repeated cross-sectional data from the Indian National Family Health Surveys conducted in 2005-06 and 2015-16. Overall, boys had greater neonatal mortality and the difference increased over time. Girls had greater postneonatal and child mortality, overall, but the difference decreased over time. A negative wealth gradient was found for all mortality outcomes for both boys and girls. Neonatal mortality was persistently greater for boys than girls over most of the household wealth distribution. Girls had greater child mortality at low levels of wealth and greater postneonatal mortality over much of the wealth distribution. The wealth gradient in neonatal mortality decreased for girls and increased for boys. Female child mortality had a substantially stronger wealth gradient but the difference decreased over the period. Not distinguishing between neonatal, postneonatal and child mortality masks important sex and socioeconomic disparities in under-5 mortality in India.

Journal of Epidemiology & Community Health: Socioeconomic and gender inequalities in neonatal, postneonatal and child mortality in India: a repeated cross-sectional study, 2005–2016

This paper examines the health impact of UK pension reforms that increased women’s State Pension age for up to six years since 2010. Exploiting an 11% increase in employment caused by the reforms, we show that rising the State Pension age reduces physical and mental health among women from routine-manual occupations. We show robust evidence that a larger increase in the State Pension age leads to larger negative health effects, resulting in a widening gap in health between women from different occupations. Our results are consistent with a 27% fall in individual incomes for women in routine-manual occupations.

We study the impact of more than 3 million Syrian refugees on Turkish businesses operating in an economy with a large informal sector. We use an instrumental variable design that relies on exogenous variations in refugee outflows from Syria and the geographic location of Arabic-speaking communities in Turkey before the conflict began. Using yearly censuses of firms, we find that refugee inflows had a positive impact on the intensive and extensive margins of production, which are highly concentrated in the informal economy. The effects are stronger for smaller firms and those that operate in the construction and hospitality industries.

Journal of Development Economics: “Blessing or burden? Impacts of refugees on businesses and the informal economy.”

In the context of fiscal austerity in many European welfare states, policy innovation often takes the form of “social investment,” a contested set of policies aimed at strengthening labor markets and fostering gender equity. Social investment policies include employment subsidies, skills training, job-finding services, early childhood education and childcare, and public support for parental leave. Given that such policies can enhance gender equity in the labor market, we analyzed the possible effects of such policies on gender health equity. Using age- and sex-stratified data from the Global Burden of Disease Study on cardiovascular disease morbidity and mortality, and policy indicators on employment supports, childcare, and parental leave from multiple sources, we find mixed effects of social investment for men versus women. Government spending on public employment services and the percent of children in early childhood education or care are associated with lower mortality rates for men, but the associations are not significant for women. Government spending on employment training and the number of eligible weeks of paid parental leave are associated with lower mortality rates for women, but the associations are not significant for men. Government spending on paid parental leave is associated with lower mortality rates for both men and women, although with a stronger association for women. Finally, government spending on early childhood education and care is associated with lower mortality rates for both men and women equally. We discuss the implications of these effects for gender equity, and of these findings for the social investment policy turn and future research on gender health equity.

Journal of Epidemiology & Community Health: “Who benefits from social investment? The gendered effects of family and employment policies on cardiovascular disease in Europe.”

Objectives: We used data from the Health and Aging in Africa: A Longitudinal Study of an INDEPTH community in South Africa (HAALSI) study in rural South Africa to examine how age and gender interact to predict older adults’ social networks and receipt of social support in rural South Africa. Method: We used regression analysis on data for 5059 adults aged over 40. We examined how network size, density, and communication and social support receipt were associated with gender and age, as well as with kin, gender and geographic composition. Results: Older respondents reported fewer important social network ties, greater network density and less frequent communication than their middle-aged peers, largely due to fewer non-kin connections. Women had smaller networks, and difference in networks size was greater between older and younger women than among men. Older women had fewer non-kin ties living in the same village than younger women; older men’s lower levels of contact relative to middle-aged men in some spheres were offset by more female and co-resident ties. Discussion: In contrast to the extant literature, older women in this study area had more limited social network and support than their male peers, and may thus benefit from targeted interventions.

The Journals of Gerontology: Series B: “Age and Gender Differences in Social Network Composition and Social Support Among Older Rural South Africans: Findings From the HAALSI Study”