WalletHub’s Vice Index: How the ‘Seven Sins’ Become 37 Measurable Metrics
Author(s): Scott Douglas Jacobsen
Publication (Outlet/Website): The Good Men Project
Publication Date (yyyy/mm/dd): 2026/03/05
In this interview, Scott Douglas Jacobsen speaks with Chip Lupo about WalletHub’s “Vice Index” and how it operationalizes the seven sins using 37 measurable indicators. Lupo says the project avoids moral judgment by translating abstract “sin” into widely recognized social harms—violence, fraud, addiction, and social disconnection—scored on a 100-point scale. Categories (Anger & Hatred, Jealousy, Excesses & Vices, Greed, Lust, Vanity, Laziness) weight equally, producing a composite index. He explains adjustments such as per-capita rates and square-root population scaling for certain venue counts, plus the rationale for Google-search interest as a comparative proxy for private behaviors.
Scott Douglas Jacobsen: How did WalletHub operationalize the seven sins?
Chip Lupo: WalletHub identified tangible metrics for each of the seven sins, allowing our team to perform a data-driven analysis and score the cities based on observable, measurable behaviors rather than moral judgments.
We used a total of 37 relevant metrics tied to crime, health, consumption, financial behavior, online search activity, and civic engagement. Each metric was scored out of 100. All metrics counted equally in their category, and the results were combined to give each category a total score of 14.3 points. Each category – Anger & Hatred, Jealousy, Excesses & Vices, Greed, Lust, Vanity, and Laziness – represents one of the seven sins.
Those category scores were averaged into a single composite measure, the WalletHub Vice Index, which captures how widespread and intense illicit activities and socially harmful excesses are in each city. This approach allowed us to move from abstract concepts like “sin” to comparable, empirical rankings grounded in real-world data.
Jacobsen: How do you address cultural/values bias baked into the concept?
Lupo: That concern is addressed by grounding the analysis in broadly recognized social harms rather than religious or moral doctrine. WalletHub does not judge personal beliefs or cultural norms. Instead, we focus on behaviors that most people, across cultures, agree are damaging when they become widespread – such as violence, fraud, addiction, and social disconnection.
The study also acknowledges that some activities aren’t inherently bad in moderation. Things like drinking, gambling, or cosmetic spending are only treated as “sinful” when data show they reach levels associated with real harm to individuals or communities. By relying on objective, publicly available metrics and applying the same standards to every city, WalletHub minimizes value judgments and keeps the rankings centered on measurable outcomes, not cultural preferences.
Jacobsen: What evidence suggests cities cause more sinful behavior rather than simply attracting it?
Lupo: The study doesn’t claim that cities cause sinful behavior. It simply shows where harmful behaviors are most concentrated and most visible.
What the evidence does suggest is that local conditions matter. The wide variation across cities, sometimes within the same state, points to factors like policy choices, economic conditions, enforcement, and access shaping how much these behaviors occur, not just who lives there.
Even if certain cities have a reputation for sinful behavior, local policymakers still have some say in what’s promoted or even tolerated moving forward.
Jacobsen: Did you control for population size, tourism volume, age distribution, income inequality, etc.?
Lupo: Most metrics were calculated on a per-capita basis, which directly adjusts for population size. For some measures, such as the number of casinos, fast-food outlets, and adult entertainment establishments, the square root of the population was used to avoid overstating differences driven purely by city size. Age effects were also accounted for in relevant metrics, such as excessive drinking and marijuana use.
Tourism and income inequality were not explicitly controlled for as standalone variables. Instead, their effects are implicitly reflected in outcome measures like crime rates, fraud complaints, gambling disorders, and debt-to-income ratios.
Jacobsen: Are violent crime and theft measured using consistent definitions?
Lupo: Yes. WalletHub relies on standardized, widely used definitions for both violent crime and theft, which allows for consistent comparisons across cities.
By using per-capita rates, data sources that include all cities, and nationally recognized definitions, WalletHub ensures that differences in rankings reflect real variation in reported behavior, not differences in how crimes are defined or counted from one city to another.
Jacobsen: For things like porn/strip-club/affair-related Google searches, how do you justify using search behavior as a proxy?
Lupo: WalletHub uses search behavior as a proxy because it offers a consistent, comparable way to measure interest in certain activities across cities, especially for behaviors that are private, stigmatized, or underreported in official statistics.
Activities tied to lust and vanity, such as pornography use or interest in strip clubs and affairs, don’t reliably show up in crime or health data. Google search interest provides an aggregated, anonymized signal of how often people in a city are actively seeking out that content. Importantly, WalletHub doesn’t look at individuals or raw volumes; it uses indexed search interest, which allows cities of different sizes to be compared on the same scale.
Used alongside indicators like the number of adult entertainment establishments or teen birth rates, search data helps fill in gaps where traditional data sources fall short, making the overall picture more complete rather than relying on any single proxy alone.
Jacobsen: If a city ranks high, what should policymakers actually do?
Lupo: A high ranking isn’t a label of moral failure. Policymakers should read it as a map of where risks are concentrated, not as a verdict on residents.
Because the index breaks results into seven categories, leaders can see which behaviors are driving the score and respond accordingly. High scores in Anger & Hatred point to the need for violence prevention, better community policing, and mental health intervention. Elevated Greed or Jealousy scores suggest focusing on fraud prevention, gambling intervention, and financial literacy education. Excesses & Vices highlight opportunities for public health responses, such as addiction treatment, harm-reduction programs, and DUI prevention. Weak performance in Laziness points to the need for investments in education, workforce participation, and civic engagement.
In short, the value of the ranking is that it turns abstract social problems into measurable pressure points. Policymakers can use it to prioritize resources, track progress over time, and learn from peer cities that score better in the same categories.
Jacobsen: How do you recommend journalists present the results responsibly?
Lupo: The results are best presented as a tool for understanding patterns, not as a moral scorecard or a “shame list” of cities.
Journalists should emphasize that the rankings measure the prevalence of certain behaviors and outcomes, not the character of residents. A high rank reflects where issues like crime, addiction, fraud, or low civic engagement are more common, not why they exist or who is to blame. Pointing readers to the category-level scores helps show nuance, since most cities perform poorly in some areas and relatively well in others.
It’s also important to highlight the methodology, especially the use of per-capita and standardized metrics, so readers understand that comparisons are data-driven.
Jacobsen: Thank you very much for the opportunity and your time, Chip.
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