Macro and micro perspectives on mortality history.

n country after country, human life expectancy has doubled in the twentieth century. Although an enorI mous amount of information has accumulated about the decline of mortality, controversy continues about how to interpret the data (Schofield 1991). Some social scientists regard decreasing mortality as a side effect of economic growth, rising incomes, and better nutrition (Komlos 1998); others stress the importance of public health (Szreter 1988; Johansson 1994). Both explanations are concerned with those changes that mattered most to most people’s lives. At the macro level, the focus is on the average person and mean values (Hill 1997,224). At the micro level, the focus is on ordinary people who lived in specific contexts. Ordinary people live their lives as males and females, passing through different age groups, living in different places, earning a living in different ways while belonging to different religions and ethnic groups. Such differences expose people to different diseases or other hazards that must be avoided, resisted, or recovered from if individuals are to continue living until old age (Johansson and Mosk 1987). To prolong their lives, people must have access to a wide range of material resources, including food, of course, but they also require knowledge about how to convert their resources into better health and the resultant longevity. The conversion of knowledge and resources into health and longevity can never be observed directly. Trained observers can see only how specific groups of people tackled their specific health/disease-related problems in diverse material and cultural circumstances (Johansson 1990). But mainstream social scientists are not trained to do highly contextualized research grounded in specific details. As Stephen Kunitz (1996, 187) observed, conventional social scientists value truth only “to the extent that it transcends time and place.” This training automatically gives them a macro-level orientation to explaining change, including mortality change, and that perspective marginalizes the value of research on small-scale populations living in specific and often distinctive contexts. Such research may even be regarded as unscientific (Kertzer and Fricke 1997), because it is bogged down in “irrelevant” details that interfere with the search for sweeping generalizations about human beings in any context. In macro history, the average person is the only person who counts. But this statistical construct is not a real person who had specific nutritional or public health problems that led to his or her premature death. The average person is not even a conscious being who frames specific problems and tries to solve them in cooperation with others. Macro-level research makes room for “relevant” details about the average person by isolating separate components, such as age, sex, family size, household type, place of residence, class, occupation, income, religion, race, and ethnicity. Subsequently, these components become independent variables that, through linear relationships, cause variation in the dependent variable (in this case, some index of mortality). The goal of macro-level research is to identify which independent variable(s) accounts for most of the observed variance in the dependent variable, irrespective of local contextual considerations (Ruzika, Wunsch, and Kane, eds. 1989; Smith 1983). The regression methods used to explain mortality history at the macro level tell us a lot about how variables behave in large data sets, whereas they shed very little light on how real people address specific health-related problems in specific circumstances. Clarification of those problems remains the goal of most micro-level mortality research. To explain problem-solving behavior, micro historians rely heavily on conventional narrative methods. They read primary sources and select a set of details that when arranged in chronological order, tell a plausible story about who did what and why and how others reacted. Story formats are based on linking details, but not in any highly standardized way. The flexibility and diversity associated with narrative methods make it difficult to see what specific stories or cases have in common, if anything (Levine 1987, 129-32). Micro-level research tends to pull researchers toward the