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Standardization to age 20 decreases mean heights of the early cohorts relative to the raw mean and raises those of later cohorts.

Otherwise, our estimates and those of Costanzo correspond fairly closely in level and overall trend. Both series indicate a cumulatively substantial increase of about 3. This trend in mean height corroborates available estimates of individual components of a biological standard of living.

If the disease environment improved, so too did real income and, with it, nutrition. Per capita availability of foodstuffs, calculated from domestic agricultural production and net imports, is estimated to have risen from approximately 2, calories per capita per day to 3, over the same period Federico Whether diet or disease was the decisive factor in improving health cannot easily be distinguished in the historical record. Massive investment in water distribution networks beginning in the s is reflected in mortality rates, but the response is subtle Caselli ; Federico , while the upward trend in heights is entirely unperturbed.

Neither does the sharp acceleration in real wage growth estimated for this period leave much trace Fenoaltea Our modeling approach offers a new perspective on improving health. The age-height profiles displayed in Figure 6 are derived from the counterfactual height distributions obtained by varying the reference age over the range from 17 to 22 years, while keeping the fraction of absentees constant.

The shifts in the age-height profiles indicate clearly that conscripts born in the first years of the twentieth century were not only taller than their grandfathers; they also reached final height much earlier. This growth anticipation effect is an aspect of the link between net nutrition and height that has been inadequately appreciated. Contrary to the hypothesis of a relatively constant coefficient of variation of height, mean and standard deviation move in opposite directions.

The age standard deviation falls by almost one centimeter from the birth cohort of to those of the early s before rising again slightly. A comparison of the counterfactual age and age series shows that this decline was largely driven by the anticipation of the AGS as net nutrition improved.

Terrenato and Ulizzi documented a convergence of the Italian height distribution toward a Gaussian shape, with both negative skewness and excess kurtosis diminishing, especially after However, they made no correction for age at measurement, explicitly claiming that it affects only the mean and not the higher moments of the distribution; nor did they correct for selection effects.

Both raw and age skewness and excess kurtosis do converge toward Gaussian values. For the birth cohorts around , for example, skewness is clearly negative at age 18 and age 20 but is slightly positive at age As for the trends, age 18 looks quite different from age 20 and age A simple interpretation of these patterns is the following.

Suppose that the peak age for nonnormality induced by the AGS is 19 in , but moves down to 16 by In this case, higher moments should display a similar trend for ages 20 and 22, which are further and further away from the AGS distortions. For age 18, by contrast, initial improvements in living conditions would at first move the height distribution into the phase of maximum nonnormality. Later, as the onset of the AGS occurs earlier and earlier, year-olds are also past this phase, and their height distribution looks more normal.

The national distributions of height discussed in the previous section mask considerable diversity at the provincial level—diversity that can be explored in depth on the basis of the new estimates developed here. This section examines the provincial trends in mean height, decomposes the variance of height at the national level into within- and between-province components, and assesses patterns of convergence and divergence at the provincial level.

Numerical values are presented in Table 1. For the cohort, the range of provincial mean height is wide: While there is considerable variability within each of the three macro-regions of North, Center, and South-Islands, a North-South gradient is evident. For the cohort, the North-South disparity is still apparent, but age mean height has increased everywhere: Clearly, net nutrition improved throughout the country over the 56 years under study here.

Drawing inferences about variation in living standards from variation in mean height is a challenging task, partly because variation in unobserved genetic potential across provinces cannot be ruled out, and partly because separating the effects of higher incomes and better health is difficult.

Our age-adjustment procedure provides new evidence that provincial disparities in mean height cannot be attributed entirely to genetic factors. Again it is the counterfactual age-height profile that yields a novel insight, this time at the provincial level.

Greater velocity at a given age indicates a late-onset AGS. Because the genetic influences controlling AGS onset are largely independent of those controlling final height, this correlation is clear evidence of environmental effects at work Tanner Although we cannot exclude a role for genetic factors in cross-province differences, within-province differences over time can be unambiguously attributed to changes in environmental factors because internal migration in this period was limited and short-range.

In several provinces, mean height increased by 5 cm or more over the sample period, suggesting that variation in environmental factors can explain significant variation in mean height. Under this assumption, which rules out interactions between the genetic component and the time trend, a comparison of provincial mean heights at a given point in time removes the common trend, since.

On the other hand, comparing changes over time in provincial mean heights removes both the common trend and the time-invariant province effects, since. Table 1 and Figure 12 present this set of differences-in-differences, with Rome taken as the reference province.

Though groups of contiguous provinces tend to share similar growth experiences, it is difficult to detect a systematic pattern in Figure 12 other than the uniformly above-average growth in the Northwest an area that came to be known as the Industrial Triangle in this period.

There is, in particular, no North-South gradient—no tendency for the shorter Southern provinces to experience above-average growth and catch up on the North. There is, in short, no convergence.

In the economic growth literature, a distinction is typically drawn between beta- and sigma-convergence, the former referring to a negative correlation of the initial level of a variable with its subsequent growth and the latter referring to a decrease in the dispersion of a variable.

As documented in the upper panel of Table 2 , neither type of convergence is observed in provincial mean heights. In the North, there is evidence of significant internal convergence, but elsewhere even within-region convergence is scant. Yet this overall lack of pattern masks a switch from convergence to divergence around The variance decomposition exercise in Figure 13 shows that within-province variability declines almost monotonically throughout the period considered.

It is between-province variability, reaching a minimum in the late s and rising from the late s, that flattens and reverses what would otherwise be a downward trend in Figure 7.

The different scales for within- and between-province variance in Figure 13 reveal the predominance of the former component in total height variability. This simply reflects the fact that individual variability due to random genetic factors, which is part of within-province variation, is large compared with systematic differences in mean height.

The switch from convergence to divergence is also evident in Figure 14 and Table 2 lower panels. The period from to displays strong convergence of all sorts: At the national level, the standard deviation of provincial mean height falls from 2. The average Southern province converges strongly on its taller Northern and Central counterparts, growing by half a centimeter more over 25 years.

The negative correlation of initial provincial mean height and its subsequent growth is visually apparent in the left panel of Figure 14 , both within and between regions. With the s begins a very different era.

Within regions, convergence largely ceases outside the North. Between regions, a process of outright divergence takes hold. The change is visually apparent in the realignment of the Northern and Southern groups of provinces in the right panel of Figure The North-South gradient in height still evident at the end of our sample period is consistent with what is known of regional economic differences at the time.

No estimates have been attempted for the 69 provinces. Northwestern Liguria was the highest-income region and also joint tallest in , while Basilicata in the South was second poorest and also second shortest. Though regional rankings by income and height broadly match, a closer look reveals some anomalies. More industry and, even, greater output per capita do not necessarily generate superior health outcomes.

The opposite can be true, for example, when rapid urbanization overwhelms public sanitation systems or causes an increase in the relative price of a nutritious diet. The height evidence suggests that the benefits of higher incomes and the diets, living conditions, and public health measures they could support outweighed such disadvantages in the North circa Mortality rates offer the only alternative indicator of health outcomes available at a disaggregated level for a wide range of years.

Postneonatal infant mortality circa , interpolated from data in Del Panta , broadly matches the pattern of regional heights. Every region of the South and Islands suffered mortality exceeding the national average. Every region of the North and Center had a death rate below the national level, with the exception of Lombardy. Anomalously tall but poor Veneto appears healthy on this measure as well, with a rate of 75 per thousand, almost 20 points below the national average of We focus on infant mortality after the first month because cold weather in the North dramatically increased mortality rates in the first days of life during the winter months, particularly in Veneto Caselli ; Del Panta As at the national level, then, the regional height record is broadly consistent with both economic and demographic indicators.

This supports the proposition that cross-province differences in mean height are informative regarding living conditions. Our new provincial estimates suggest that there may have been considerable variation in living conditions even within regions. In Sicily, for example, mean heights range from There is much less data and considerably less agreement about regional economic trends in earlier periods. In the absence of firm quantitative foundations, interpretations of regional developments after Italian Unification in have been derived more from theory than evidence.

And they have tended to focus on broad North-South comparisons. One school of thought has seen regional disparities as growing from deep institutional or geographical roots and being significant already at the time at the time of Unification. After Unification, disparities gradually widened as the North built on its initial advantages. An alternative view sees North-South divergence as commencing only with Unification, in fact being caused directly by it.

In some accounts, fiscal policy drained resources from the South to finance investments that favored Northern industry, which also benefited from tariff protection. Recent studies by Fenoaltea They argued that a North-South gap emerged only 20 years after Unification, beginning in the s with an acceleration of industrialization in the North.

Veneto in particular had the lowest regional mortality rate among both infants aged 2—12 months and children aged 1—5 years. The advantage for Northern newborns was even more pronounced at this early date, however.

Though mortality in the first month of life declined everywhere in the decades following Unification, progress was most dramatic in the North. The — convergence in provincial mean heights fits none of the accounts of regional economic development. None envisions a period in which Southern regions benefited disproportionately from economic growth, from public infrastructure investment or, for that matter, from exogenous changes in the disease environment or relative price of protein-rich food.

The possibility of strong nonlinearity in the relationship between height and net nutrition means that we cannot rule out a generalized, proportionate improvement in living conditions producing convergence. Still, the new evidence on heights suggests that a reassessment of trends in regional economic development in the first decades after Unification may be warranted.

The post divergence of mean heights, by contrast, fits with most of the economic historiography on the period. It is worth reiterating that heights in the South and throughout Italy continued to improve after Though height and health cannot be presumed to track income unerringly, this suggests the economic decline of the South was only relative to a rapidly growing North Vecchi and Coppola Studies of human stature have frequently relied on the explicit assumption that heights follow a normal distribution and the typically implicit premise that covariates affect only the mean of the distribution.

The evidence developed here, on the basis of a modeling technique that eschews such a priori restrictions, indicates that both assumptions are problematic. In particular, the adolescent growth spurt AGS has been shown to systematically distort the distribution of heights by increasing dispersion, negative skewness, and excess kurtosis.

In the conditions of net nutritional stress typical of the period studied, the effects of the AGS were maximal in the late teens and lingered into the early 20s. Our semiparametric model of age effects on the height distribution offers more than just a way of controlling for age at measurement; it generates substantive insights into the effects of environmental conditions on human growth.

Using our province-specific estimates to construct counterfactual height distributions at different ages, we are able to generate age-height profiles. These profiles indicate that the AGS was systematically later in provinces with shorter mean heights, implying environmental rather than purely genetic influences on provincial mean stature. They also show that improving net nutrition not only increased final height but also led to an earlier onset of puberty and the AGS.

Our age-specific estimates of trends in the higher moments of the distribution at the national level confirm this finding. They indicate that the period of maximum AGS-induced distortion of the distribution shifted from above to below 18 years of age. Our age-adjusted, smoothed, provincial height distributions also offer new insights into regional economic development in nineteenth century Italy.

Post divergence accords with the perception of widening economic disparities between North and South in this period. The continued increase of heights everywhere even in this period is a useful reminder that regional divergence was a relative rather than an absolute phenomenon. Pre convergence in height is an entirely novel finding, one indicating that presumptions of constant or widening economic disparities may need to be reassessed.

We also thank the Italian National Institute of Statistics Istat , and especially Franco Ottone, for providing the geospatial data sets needed to construct the maps in the article. National Center for Biotechnology Information , U. Journal List Demography v. Author information Copyright and License information Disclaimer. This article has been cited by other articles in PMC. Abstract Researchers modeling historical heights have typically relied on the restrictive assumption of a normal distribution, only the mean of which is affected by age, income, nutrition, disease, and similar influences.

Open in a separate window. Recruitment Procedures Statistical modeling of the Torre report data requires an understanding of the recruitment procedures that generated them. Data Problems Various problems in the Torre report data require attention: Adjusting for Age and Selection Effects The unobservable individual measurements underlying the tabulations in the Torre reports may be regarded as draws from a probability distribution that represents the variability of height across the surviving members of a cohort at the time when they are measured.

Provincial Level The national distributions of height discussed in the previous section mask considerable diversity at the provincial level—diversity that can be explored in depth on the basis of the new estimates developed here. Height, Health, and Regional Economic Development The North-South gradient in height still evident at the end of our sample period is consistent with what is known of regional economic differences at the time.

Daniele V, Malanima P. Eveleth P, Tanner JM. Worldwide Variation in Human Growth. Cambridge University Press; Measuring Regional Disparities in Income. Historical Lessons of Pan-European Development. University of Lund; The Age of Mass Migration: Causes and Economic Impact.

Oxford University Press; Istat Sommario di Statistiche Storiche [Summary of historical statistics]. Istituto Centrale di Statistica. Antropometria Militare [Military anthropometry]. Parts I and II.

University of Chicago Press; A History of the Study of Human Growth. Physical Growth From Conception to Maturity.

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